CN115542215A - System and method for magnetic resonance imaging - Google Patents

Abstract

The present specification provides a system for MRI. The system comprises an acquisition module and a quantitative measurement module. The acquisition module may be configured to acquire at least two sets of k-space data corresponding to at least two frames. Each of at least two sets of K-space data is acquired simultaneously from at least two slice positions of the subject using a magnetic resonance imaging scanner in one of at least two frames, with a wait time after application of a preparation pulse in the frame. The quantitative measurement module may be for generating at least two quantitative maps of at least two slice positions based on the at least two sets of k-space data. Applying phase modulation to at least one target layer position of the at least two layer positions for inter-layer separation in the at least two frames.

Description

System and method for magnetic resonance imaging

Priority declaration

This specification claims priority to U.S. application No. US17/305,055, filed on 30/06/2021, which is a partial continuation of U.S. application No. US16/823,274, filed on 18/03/2020, or 16/658,297, filed on 21/10/2019, the contents of all three U.S. applications being incorporated herein by reference.

Technical Field

The present description relates generally to Magnetic Resonance Imaging (MRI), and more particularly to systems and methods for simultaneously making quantitative measurements of multiple slice locations of a subject.

Background

MRI is an important clinical tool for diagnosing and/or treating diseases. In some cases, one or more quantitative parameters, such as longitudinal relaxation time (T1), transverse relaxation time (T2) and transverse relaxation decay (T2 ×) of the object, may be determined by performing an MRI scan of the object. The quantitative parameters may reflect physiological characteristics of the subject and may be used for disease diagnosis. Traditionally, quantitative measurements are made separately for different layer locations of the object, which is inefficient. Multi-slice simultaneous (SMS) imaging technology, otherwise known as multiband imaging technology, is a promising technique to accelerate MR scanning, allowing simultaneous excitation of multiple slice locations. It is therefore desirable to provide systems and methods for quantitative measurement of objects with improved efficiency by incorporating SMS imaging techniques.

Disclosure of Invention

According to another aspect of the present specification, an MRI system is provided. The system may include an acquisition module and a quantitative measurement module. The acquisition module may be configured to acquire at least two sets of K-space data corresponding to at least two frames, each of the at least two sets of K-space data being acquired simultaneously from at least two slice positions of the subject using the magnetic resonance imaging scanner in one of the at least two frames with a latency after applying the preparation pulse. The quantitative measurement module may be configured to generate at least two quantitative maps of the at least two slice locations based on the at least two sets of k-space data. Applying phase modulation to at least one target layer location of the at least two layer locations for interlayer separation in the at least two frames.

In some embodiments, for each of the at least one target layer locations, the phase of the target layer location is modulated along the spatial dimension during each of the at least two frames according to the phase modulation mechanism of the frame.

In some embodiments, for each of the at least one target layer location, a phase of the target layer location is modulated along a time dimension such that a phase modulation mechanism of a pair of adjacent frames of the at least two frames is different.

In some embodiments, the at least two target layer images for the layer location are generated together with at least two quantification maps for the at least two layer locations.

In some embodiments, to generate at least two quantitative maps for at least two layer locations based on at least two sets of k-space data, the at least one processor may be configured to instruct the system to determine one or more reconstruction parameters based on the at least two sets of k-space data, and construct an optimization function comprising the quantitative maps for the at least two layer locations, at least two target layer images for the at least two layer locations, the one or more reconstruction parameters, and the at least two sets of k-space data. For each layer position of the plurality of layer positions, the at least one processor may be configured to generate the at least two quantitative maps and the at least two target layer images for the at least two layer positions by solving the optimization function.

In some embodiments, the optimization function is constructed based on a signal model that constructs a relationship between the latency and quantitative parameters of the quantitative map corresponding to the at least two layer positions.

In some embodiments, to determine one or more reconstruction parameters based on at least two sets of k-space data, for each layer position of the at least two layer positions, the at least one processor may be configured to instruct the system to generate a reference layer image for the layer position based on the at least two sets of k-space data, and to treat at least two coil sensitivity maps corresponding to each layer position of the at least two layer positions as part of the one or more reconstruction parameters based on the reference layer image for the at least two layer positions.

In some embodiments, for each of the at least two frames, the corresponding set of k-space data is a set of undersampled k-space data collected according to the intra-frame undersampling mode.

In some embodiments, the undersampling patterns of a pair of adjacent frames of the at least two frames are interleaved.

In some embodiments, the preparation pulse comprises an inversion pulse and the quantitative map for each of the at least two layer locations comprises a T1 map.

According to another aspect of the present description, a non-transitory computer-readable storage medium is provided that includes a set of instructions for MRI. A set of instructions, when executed by at least one processor of a system, may cause the system to perform a method. The method may include acquiring at least two sets of K-space data corresponding to at least two frames, wherein each of the at least two sets of K-space data is acquired simultaneously from at least two slice positions of the subject using a magnetic resonance imaging scanner in one of the at least two frames with a latency after applying the preparation pulse. The method may further comprise generating at least two quantitative maps of the at least two layer positions based on the at least two sets of k-space data, wherein in the at least two frames, phase modulation is applied to at least one target layer position of the at least two layer positions for inter-layer separation.

Additional features of some of the description may be set forth in the description which follows. Additional features of some portions of this description will be apparent to those skilled in the art upon examination of the following description and accompanying drawings or upon production or operation of the embodiments. The features of the present description may be implemented by practice or use of the methodologies set forth in the detailed examples discussed below various aspects of the tools and combinations.

Drawings

This description will be further described by way of exemplary embodiments. These exemplary embodiments will be described in detail by means of the accompanying drawings. These embodiments are non-limiting exemplary embodiments in which like reference numerals represent similar structures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic view of an exemplary MRI system shown in accordance with some embodiments of the present description;

FIG. 2 is a schematic view of an exemplary MRI scanner shown in accordance with some embodiments of the present description;

FIG. 3 is a schematic diagram of exemplary hardware and/or software components of a computing device shown in accordance with some embodiments of the present description;

FIG. 4 is a schematic diagram of exemplary hardware and/or software components of a mobile device shown in accordance with some embodiments of the present description;

FIG. 5 is a block diagram of an exemplary processing device shown in accordance with some embodiments of the present description;

FIG. 6 is a flow diagram of an exemplary process for multi-slice simultaneous MRI, shown in accordance with some embodiments of the present description;

FIG. 7 is a schematic diagram of an exemplary bSSFP pulse sequence shown in accordance with some embodiments of the present description;

FIGS. 8A and 8B are exemplary aliased images of two slice locations in the heart, shown in accordance with some embodiments of the present description;

FIGS. 9A and 9B are exemplary reference layer images of two layer locations in a heart, according to some embodiments of the present description;

FIG. 10 is an exemplary cardiac layer image shown in accordance with some embodiments of the present description;

FIG. 11 is a schematic diagram of an exemplary bSSFP pulse sequence shown in accordance with some embodiments of the present description;

FIG. 12 is a schematic diagram of an exemplary FSE pulse sequence shown in accordance with some embodiments of the present description;

fig. 13 is a schematic diagram of an exemplary EPI pulse sequence shown in accordance with some embodiments of the present description;

FIG. 14 is a flow chart of an exemplary process for multi-slice simultaneous MRI, shown in accordance with some embodiments of the present description;

FIG. 15 is a flow diagram of an exemplary process for reconstructing at least two reference layer images, according to some embodiments of the present description;

fig. 16 is a schematic diagram of an exemplary phase modulation and undersampling pattern in an MR scan, shown in accordance with some embodiments of the present description;

FIG. 17 is a schematic diagram of an exemplary process for generating a reference layer image, shown in accordance with some embodiments of the present description;

FIG. 18 is an illustration of an exemplary phase modulation mechanism for a first layer position and a second layer position in a frame, shown in accordance with some embodiments of the present description;

FIG. 19 is a slice image corresponding to the same cardiac phase of a patient, shown in accordance with some embodiments of the present description;

FIG. 20 is an exemplary image sequence of two slice positions of a patient's heart shown in accordance with some embodiments of the present description;

FIG. 21 is a flow diagram of an exemplary process for generating at least two quantitative maps of at least two layer locations, shown in accordance with some embodiments of the present description;

FIG. 22 is a flow diagram of an exemplary process of at least two quantitative maps for at least two layer locations, shown in accordance with some embodiments of the present description;

FIG. 23 is a schematic diagram of an exemplary pulse sequence shown in accordance with some embodiments of the present description; and

fig. 24 is a schematic diagram of an exemplary pulse sequence shown in accordance with some embodiments of the present description.

Detailed Description

Provided herein are systems and methods for non-invasive biomedical imaging, e.g., for disease diagnosis or research purposes. Although the systems and methods disclosed herein are described primarily with respect to quantitative measurement and multi-slice (SMS) imaging of a subject in a Magnetic Resonance Imaging (MRI) system. It should be understood that this is for illustrative purposes only. The systems and methods of the present description may be applied to any other imaging system. In some embodiments, the imaging system may include a single modality imaging system and/or a multi-modality imaging system. The single modality imaging system may comprise, for example, an MRI system. The multi-modality imaging system can include, for example, an X-ray imaging magnetic resonance imaging (X-ray-MRI) system, a single photon emission computed tomography magnetic resonance imaging (SPECT-MRI) system, a digital subtraction angiography magnetic resonance imaging (DSA-MRI) system, a computed tomography magnetic resonance imaging (MRI-CT) system, a positron emission tomography magnetic resonance imaging (PET-MRI) system, and the like.

One aspect of the present description relates to systems and methods for simultaneously imaging at least two (multiple) slice locations of an object using an MRI scanner. The at least two (plurality of) layer locations may include a first layer location and at least one second layer location. Typically, an additional reference scan may need to be performed to obtain reference data for each layer position for inter-layer separation. For example, reference slice images of at least two (multiple) slice locations can be reconstructed and coil sensitivity profiles of different receive coils can be determined. The slice image for each individual slice position can be separated from the aliased image acquired in the SMS imaging based on the coil sensitivity distribution. However, the additional reference scan may result in additional scan time and compromise the advantages of SMS imaging.

To avoid the need for additional reference scans, the systems and methods of the present description can utilize auto-calibrated multi-band imaging techniques. For example, in each of at least two (multi) frames, the systems and methods may cause the MRI scanner to apply at least two (multiple) phase-encoding (PE) steps to each layer position to acquire a set of echo signals. In each of the at least two (multi) frames, a phase-modulated magnetic field gradient (also referred to simply as a phase-modulated gradient) may be applied in each of at least some of the at least two (multi) PE steps such that for a plurality of PE steps corresponding to PE lines at the same location in k-space and applied in a pair of the at least two (multi) frames, a plurality of phase differences, each of which is a difference of at least one second layer location and the first layer location at one of the at least two (multi) PE steps, are different.

By applying a phase modulation gradient, the system and method may reconstruct one or more images based on a set of echo signals acquired in a frame without additional reference scans, where each layer image may represent a single layer location in a frame. For example, the system and method may reconstruct aliased images of at least two (more) layer locations in each frame based on a corresponding set of echo signals and generate reference layer images of the at least two (more) layer locations based on the aliased images (e.g., by performing a linear combination of the aliased images). The system and method may further reconstruct a layer image based on the aliased image and the reference layer image. As such, the system and method may eliminate the need for an additional reference scan, shorten scan time, and/or improve imaging efficiency and/or patient experience.

Furthermore, in some embodiments, phase modulation herein may be achieved by phase modulation gradients applied by the Z-coil of the MRI scanner alone or in combination with phase modulated Radio Frequency (RF) excitation pulses. Conventional methods of auto-calibrating phase modulation in SMS during at least two frames (multiframes), such as the controlled aliasing parallel acceleration imaging (CAIPIRINHA) technique using only phase-modulated RF excitation pulses, can limit the pulse sequence without echo sequences, each of which acquires only one PE-line data. The systems and methods provided herein may be applicable not only to spoiling gradient echo (gre) sequences, but also to balancing steady-state free-precession (bSSFP) pulse sequences. The disclosed technique is also applicable to sequences having echo sequences, such as Echo Planar Imaging (EPI) pulse sequences and Fast Spin Echo (FSE) pulse sequences.

In some embodiments, to further speed up the MR scanning process, the systems and methods of the present specification may utilize ATOMICS, which combines an auto-calibrated multi-band imaging technique with a Compressed Sensing (CS) technique. For example, the systems and methods may acquire at least two sets of undersampled k-space data corresponding to at least two (multiple) frames. Each of a plurality of sets of undersampled k-space data may be acquired simultaneously from a plurality of slice positions of the subject in one of at least two (or more) frames using the MRI scanner. Each of the at least two sets of undersampled k-space data may be acquired from at least two (more) layer locations of the object in each of at least two (more) frames using the MRI scanner. The system and method may reconstruct at least two reference layer images based on at least two (multi) frames of undersampled k-space data. Each of the at least two reference layer pictures may represent one of the at least two (or more) layer locations of more than one of the at least two (or more) frames. The system and method may also reconstruct at least two image sequence(s) based on the undersampled k-space data and the at least two reference layer images. Each of the at least two (or more) image sequences may correspond to one of the at least two (or more) layer positions and comprise at least two layer images of the corresponding layer position in at least two (or more) frames.

By using ATOMICS, a single-band reference slice image can be generated based on the undersampled k-space data, thereby eliminating the need for an additional reference scan. Furthermore, only a part of the k-space data may need to be collected by the CS technique, which results in higher acceleration and improved imaging efficiency. For example, if two slice positions of the patient's heart are scanned simultaneously with an in-plane undersampling factor of 8 (e.g., 15 lines per frame), a 16-fold acceleration may be achieved. Full cardiac cine imaging may be completed in a short time (e.g., a time below a threshold, such as 12 seconds) to allow the patient to breathe freely during the scan.

In some embodiments, the systems and methods of the present description can simultaneously generate a quantitative map of at least two (multiple) layer locations of an object by combining SMS imaging techniques and quantitative measurement techniques. For example, the systems and methods may acquire at least two sets of k-space data corresponding to at least two frames (multiframes). Each of the at least two sets of K-space data may be acquired simultaneously from at least two (multiple) slice positions of the subject using the MRI scanner in one of at least two (multiple) frames with a latency after application of the preparation pulse. The system and method may generate at least two quantification maps for at least two (multiple) slice locations based on at least two sets of k-space data. In some embodiments, the latency in at least two (multiple) frames may be different. In at least two (multi) frames, phase modulation is applied to at least one target layer position of at least two (multiple) layer positions for interlayer separation. In some embodiments, the at least two target layer images for the at least two layer locations(s) may be generated together with the at least two quantification maps for the at least two layer locations(s).

Traditionally, the different layer positions are measured quantitatively separately. For example, for each slice position, k-space data corresponding to different inversion times may be acquired by an MRI scan of the slice position, and a T1 map of the slice position may be determined based on the k-space data according to a curve fitting algorithm. This process takes a long scanning time, which brings an uncomfortable scanning experience to the subject. The system and method can simultaneously generate quantitative maps of multiple layer locations by utilizing SMS imaging techniques, which is more efficient by, for example, reducing scan time, as compared to conventional quantitative measurement techniques.

In addition, the system and method can incorporate and take advantage of automatically calibrated multi-band imaging techniques and/or CS techniques. With CS techniques, only partial k-space data (i.e., undersampled k-space data) may need to be collected, thereby improving imaging efficiency. The automatically calibrated multiband imaging technique can be implemented by applying phase modulation on one or more of the at least two (multiple) layer locations for interlayer separation, which can avoid the extra scan required to generate the reference layer image and avoid errors that may occur in the extra scan.

FIG. 1 is a schematic diagram of an exemplary MRI system 100 shown in accordance with some embodiments of the present description. As shown in fig. 1, the MRI system 100 may include an MRI scanner 110, a processing device 120, a storage device 130, one or more terminals 140, and a network 150. In some embodiments, the scanner 110, the processing device 120, the storage device 130, and the terminal 140 may be connected and/or in communication with each other via a wireless connection, a wired connection, or a combination thereof. The connections between components in the MRI system 100 may be variable. For example, the MRI scanner 110 may be connected to the processing device 120 through the network 150. As another example, the MRI scanner 110 may be directly connected to the processing device 120.

The MRI scanner 110 may be configured to scan a subject (or a portion of a subject) to acquire image data, such as echo signals (or MRI signals) associated with the subject. For example, the MRI scanner 110 may detect at least two (multiple) echo signals by applying an MR pulse sequence on the object. In some embodiments, the MRI scanner 110 may include, for example, a main magnet, gradient coils (or also referred to as spatial encoding coils), radio Frequency (RF) coils, and the like, as described in fig. 2. In some embodiments, the MRI scanner 110 may be a permanent magnet MRI scanner, a superconducting electromagnet MRI scanner, or a resistive electromagnet MRI scanner, among others, depending on the type of main magnet. In some embodiments, the MRI scanner 110 may be a high-field MRI scanner, a mid-field MRI scanner, a low-field MRI scanner, and the like, depending on the magnetic field strength.

The object scanned by the MRI scanner 110 may be biological or non-biological. For example, the object may include a patient, an artificial object, and the like. As another example, the object may include a particular portion, organ, tissue, and/or physical point of the patient. By way of example only, the object may include a head, brain, neck, body, shoulder, arm, chest, heart, stomach, blood vessels, soft tissue, knee joint, foot, and the like, or a combination thereof.

For ease of illustration, a coordinate system 160 including an X-axis, a Y-axis, and a Z-axis is provided in FIG. 1. The X and Z axes shown in fig. 1 may be horizontal and the Y axis may be vertical. As shown, the positive X-direction along the X-axis may be a direction from the right side to the left side of the MRI scanner 110, as viewed from a direction facing the front of the MRI scanner 110; the positive Y-direction along the Y-axis shown in fig. 1 may be from the lower to the upper portion of the MRI scanner 110; the positive Z-direction along the Z-axis shown in fig. 1 may refer to the direction in which a subject moves out of the scanning tunnel (or called bore) of the MRI scanner 110. More description of the MRI scanner 110 may be found elsewhere in this specification. See, for example, fig. 2 and its description.

In some embodiments, the MRI scanner 110 may be instructed to select an anatomical layer of the subject in a slice selection direction and scan the anatomical layer to acquire at least two (multiple) echo signals from the layer. During scanning, spatial encoding within a layer may be achieved by spatial encoding coils (e.g., X-coils and Y-coils) in both the phase encoding direction and the frequency encoding direction. The echo signals may be sampled and the corresponding sampled data may be stored into a k-space matrix for image reconstruction. For purposes of illustration, the slice selection direction herein may correspond to the Z-direction defined by coordinate system 160 and the Kz-direction in k-space; the phase encoding direction may correspond to the Y direction defined by coordinate system 160 and the Ky direction in k-space; and the frequency encoding direction may correspond to the X direction defined by coordinate system 160 and the Kx direction in k-space. It should be noted that the layer selection direction, the phase encoding direction and the frequency encoding direction can be modified according to actual needs, and such modifications may be made without departing from the scope of the present description. More description of the MRI scanner 110 may be found elsewhere in this specification. See, for example, fig. 2 and its description.

The processing device 120 may process data and/or information acquired from the MRI scanner 110, the storage device 130, and/or the terminal 140, and the processing device 120 may simultaneously generate at least two quantitative maps for at least two (multiple) layer locations based on at least two sets of k-space data for the at least two (multiple) layer locations acquired in at least two (multiple) frames (frames). In some embodiments, the processing device 120 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, the processing device 120 may be local or remote. For example, the processing device 120 may access information and/or data from the MRI scanner 110, the storage device 130, and/or the terminal 140 via the network 150. As another example, the processing device 120 may be directly connected to the MRI scanner 110, the terminal 140, and/or the storage device 130 to access information and/or data. In some embodiments, the processing device 120 may be implemented on a cloud platform. For example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, and the like, or combinations thereof. In some embodiments, processing device 120 may be implemented by a computing device 300 having one or more components as described in fig. 3.

Storage device 130 may store data, instructions, and/or any other information. In some embodiments, the storage device 130 may store data acquired from the MRI scanner 110, the processing device 120, and/or the terminal 140. In some embodiments, storage device 130 may store data and/or instructions that processing device 120 may execute, or that processing device 120 may use to perform, the example methods described herein.

In some embodiments, the storage device 130 may be connected to the network 150 to communicate with one or more other components in the MRI system 100 (e.g., the MRI scanner 110, the processing device 120, and/or the terminal 140). One or more components of the MRI system 100 may be via a network 150 access data or instructions stored in the storage device 130. In some embodiments, the storage device 130 may be part of the processing device 120 or the terminal 140.

The terminal 140 may be configured to enable user interaction between a user and the MRI system 100. For example, the terminal 140 may receive instructions from a user to cause the MRI scanner 110 to scan an object. For another example, the terminal 140 may receive a processing result (e.g., a layer image characterizing a layer position of the object) from the processing device 120 and display the processing result to the user. In some embodiments, the terminal 140 may be connected to and/or in communication with the MRI scanner 110, the processing device 120, and/or the storage device 130. In some embodiments, the terminal 140 may include a mobile device 140-1, a tablet computer 140-2, a laptop computer 140-3, or the like, or combinations thereof. In some embodiments, the terminal 140 may include an input device, an output device, and the like. The input devices may include alphanumeric and other keys that may be entered via a keypad, a touch screen (e.g., with tactile or haptic feedback), voice input, eye-tracking input, brain-monitoring system input, or any other similar input mechanism. Input information received through the input device may be sent to the processing device 120 for further processing via, for example, a bus. Other types of input devices may include cursor control devices, such as a mouse, a trackball, or cursor direction keys, among others. Output devices may include a display, speakers, printer, etc., or a combination thereof. In some embodiments, the terminal 140 may be part of the processing device 120 or the MRI scanner 110.

The network 150 may include any suitable network that may facilitate information and/or data exchange for the MRI system 100. In some embodiments, one or more components of the MRI system 100 (e.g., the MRI scanner 110, the processing device 120, the storage device 130, the terminal 140, etc.) may communicate information and/or data with one or more other components of the MRI system 100 via the network 150. For example, the processing device 120 may acquire image data (e.g., echo signals) from the MRI scanner 110 via the network 150. As another example, processing device 120 may obtain user instructions from terminal 140 via network 150.

The description is intended to be illustrative, and not to limit the scope of the specification. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and characteristics of the exemplary embodiments described herein may be combined in various ways to obtain additional and/or alternative exemplary embodiments. In some embodiments, the MRI system 100 may include one or more additional components and/or may omit one or more of the components described above. Additionally or alternatively, two or more components of the MRI system 100 may be integrated into a single component. For example, the processing device 120 may be integrated into the MRI scanner 110. For another example, a component of the MRI system 100 may be replaced by another component capable of performing the function of the component. In some embodiments, storage 130 may be a data store comprising a cloud computing platform, such as a public cloud, a private cloud, a community and hybrid cloud, and the like. However, such changes and modifications do not depart from the scope of the present specification.

Fig. 2 is a schematic diagram of an exemplary MRI scanner 110 shown in accordance with some embodiments of the present description. One or more components of the MRI scanner 110 are shown in fig. 2. As shown, the main magnet 201 can generate a first magnetic field (or referred to as a main magnetic field) that can be applied to a subject (or referred to as a subject) exposed within the field. The main magnet 201 may comprise a resistive magnet or a superconducting magnet, both of which require a power supply (not shown) to operate. Optionally, the main magnet 201 may comprise a permanent magnet. The main magnet 201 may include a hole to place a subject inside. The main magnet 201 can also control the homogeneity of the generated main magnetic field. Some shim coils may be in the main magnet 201. Shim coils placed in the gaps of the main magnet 201 can compensate for inhomogeneities in the magnetic field of the main magnet 201. The shim coil may be charged by a shim power supply.

Gradient coils 202 may be located within the main magnet 201. The gradient coil 202 may generate a second magnetic field (or so-called gradient field, including gradient fields Gx, gy, and Gz). The second magnetic field may be superimposed on and distort the main field generated by the main magnet 201 such that the magnetic orientation of the protons of the object may vary depending on their position within the gradient field, thereby encoding spatial information into MR signals generated by the region of the imaging object. The gradient coils 202 may include X-coils (e.g., for generating a gradient field Gx corresponding to the X-direction), Y-coils (e.g., for generating a gradient field Gy corresponding to the Y-direction), and/or Z-coils (e.g., for generating a gradient field Gz corresponding to the Z-direction) (not shown in fig. 2). In some embodiments, the Z coil may be based on a circular (MaxWell) coil design, while the X and Y coils may be based on a saddle (Golay) coil configuration design. Three sets of coils may generate three different magnetic fields for position encoding. The gradient coils 202 may allow spatial encoding of the MR signals for image construction. The gradient coil 202 may be connected to one or more of an X-gradient amplifier 204, a Y-gradient amplifier 205, or a Z-gradient amplifier 206. One or more of the three amplifiers may be connected to a waveform generator 216. The waveform generator 216 may generate gradient waveforms that are applied to the X-gradient amplifier 204, the Y-gradient amplifier 205, and/or the Z-gradient amplifier 206. The amplifier may amplify the waveform. The amplified waveform may be applied to one of the gradient coils 202 to generate a magnetic field in the X-axis, Y-axis, or Z-axis, respectively. The gradient coils 202 may be designed for a closed bore MRI scanner or an open bore MRI scanner. In some cases, all three sets of coils of the gradient coils 202 may be excited and thus may generate three gradient fields. In some embodiments of the present description, the X-coil and the Y-coil may be energized to generate gradient fields in the X-direction and the Y-direction. As used herein, the X-axis, Y-axis, Z-axis, X-direction, Y-direction, and Z-direction in the description of fig. 2 are the same as or similar to those described in fig. 1.

In some embodiments, a Radio Frequency (RF) coil 203 may be located within the main magnet 201 and function as a transmitter, a receiver, or both. The RF coil 203 may be connected with RF electronics 209, and the RF electronics 209 may be configured or used as one or more Integrated Circuits (ICs) to function as a waveform transmitter and/or a waveform receiver. RF electronics 209 may be connected to a Radio Frequency Power Amplifier (RFPA) 207 and an analog-to-digital converter (ADC) 208.

When used as a transmitter, the RF coil 203 may generate an RF signal that provides a third magnetic field for generating an MR signal related to a region of the object image. The third magnetic field may be perpendicular to the main magnetic field. The waveform generator 216 may generate RF pulses. The RF pulses may be amplified by the RF pa 207, processed by the RF electronics 209, and applied to the RF coil 203 to generate RF signals responsive to the powerful current generated by the RF electronics 209 based on the amplified RF pulses.

When used as a receiver, the RF coil may be responsible for detecting the echo signals. After excitation, echo signals produced by the subject may be sensed by the RF coil 203. The receive amplifier may then receive the sensed echo signals from the RF coil 203, amplify the sensed echo signals, and provide the amplified echo signals to the ADC 208. The ADC 208 may convert the echo signal from an analog signal to a digital signal. The digital echo signals may then be sent to the processing device 120 for sampling.

In some embodiments, the gradient coils 202 and the RF coils 203 may be positioned circumferentially relative to the subject. Those skilled in the art understand that the main magnet 201, gradient coils 202, and RF coils 203 can be disposed in various configurations around the object.

In some embodiments, the RF pa 207 may amplify the RF pulses (e.g., power of the RF pulses, voltage of the RF pulses) such that amplified RF pulses are generated to drive the RF coil 203.Rf pa 207 may comprise a transistor-based rf pa, a vacuum tube-based rf pa, the like, or any combination thereof. The transistor-based RFPA may include one or more transistors. Vacuum tube based RFPAs may include triodes, tetrodes, klystrons, etc., or any combination thereof. In some embodiments, the RFPA 207 may comprise a linear RFPA or a non-linear RFPA. In some embodiments, the RFPA 207 may include one or more RFPAs.

In some embodiments, the MRI scanner 110 may also include an object positioning system (not shown). An object positioning system may include an object support and a transport apparatus. The subject may be placed on a subject support and positioned within the bore of the main magnet 201 by a transport device.

An MRI system (e.g., MRI system 100 disclosed in this specification) may generally be used to acquire internal images from a patient for a particular region of interest (ROI), which may be used for purposes such as diagnosis, therapy, or a combination thereof. An MRI system includes a main magnet (e.g., main magnet 201) assembly for providing a strong, uniform main magnetic field to align individual magnetic moments of hydrogen atoms within a patient. In this process, the hydrogen atoms oscillate around their poles at their characteristic larmor frequency. If the tissue corresponds to another magnetic field tuned to the Larmor frequency, the hydrogen atoms absorb additional energy, thereby rotating the net aligning moment of the hydrogen atoms. The additional magnetic field may be provided by an RF excitation signal (e.g., an RF signal generated by the RF coil 203). When the additional magnetic field is removed, the magnetic moments of the hydrogen atoms rotate back into alignment with the main magnetic field, thereby transmitting an echo signal. The echo signals are received and processed to form an MR image. T1 relaxation can be the process of net magnetization increase/return to an initial maximum parallel to the main magnetic field. T1 may be the time constant for the regrowth of longitudinal magnetization (e.g., along the main magnetic field). The T2 relaxation may be a process of transverse component decay or dephasing of the magnetization. T2 may be the time constant of the transverse magnetization decay/dephasing.

If the main magnetic field is uniform throughout the patient's body, the RF excitation signal can non-selectively excite all the hydrogen atoms in the sample. Thus, for imaging a particular part of the patient's body, magnetic field gradients Gx, gy, and Gz in the x, y, and z directions (e.g., generated by the gradient coils 202) having a particular time, frequency, and phase may be superimposed on the uniform magnetic field such that the RF excitation signals excite H atoms in a desired slice within the patient's body and unique phase and frequency information is encoded in the MR signals based on the location of the hydrogen atoms in the "image slice". Typically, an image portion of the patient's body is scanned through a series of measurement cycles in which the RF excitation signals and magnetic field gradients, gx, gy, and Gz, vary according to the MRI image protocol being used. Protocols may be designed for one or more tissues to be an image, disease, and/or clinical scenario. A protocol may include a number of pulse sequences oriented in different planes and/or different parameters. The pulse sequence may include a spin echo sequence, a gradient echo sequence, a diffusion sequence, an Inversion Recovery (IR) sequence, and the like, or any combination thereof. For example, the spin echo sequence may include Fast Spin Echo (FSE), turbo Spin Echo (TSE), fast acquisition with relaxation enhancement (RARE), half Fourier acquisition single turbine spin echo (HASTE), turbo Gradient Spin Echo (TGSE), and the like, or any combination thereof. The protocol may also include information about image contrast and/or ratio, ROI, slice thickness, image type (e.g., T1 weighted image, T2 weighted image, proton density weighted image, etc.), T1, T2, echo type (spin echo, fast Spin Echo (FSE), fast recovery FSE, single shot FSE, gradient callback echo, fast image with steady state motion, etc.), flip angle value, acquisition Time (TA), echo Time (TE), repetition Time (TR), echo chain length (ETL), phase number, excitation times (NEX), inversion time, bandwidth (e.g., RF receiver bandwidth, RF transmitter bandwidth, etc.), etc., or any combination thereof.

Fig. 3 is a schematic diagram of exemplary hardware and/or software components of a computing device 300 shown in accordance with some embodiments of the present description. Computing device 300 may be used to implement any of the components of MRI system 100 as described herein. For example, processing device 120 and/or terminal 140 may be implemented on computing device 300 via their hardware, software programs, firmware, or combinations thereof, respectively. Although only one such computing device is illustrated for convenience, the computer functions associated with the MRI system 100 described herein may be implemented in a distributed manner across a plurality of similar platforms to distribute processing loads. As shown in FIG. 3, computing device 300 may include a processor 310, memory 320, input/output (I/O) 330, and communication ports 340.

The processor 310 may execute computer instructions (program code) and perform the functions of the processing device 120 in accordance with the techniques described herein. Computer instructions may include routines, programs, objects, components, signals, data structures, procedures, modules, and functions that perform particular functions described herein. For example, the processor 310 may process image data acquired from the MRI scanner 110, the terminal 140, the storage device 130, and/or any other component of the MRI system 100.

For illustrative purposes only, only one processor is depicted in computing device 300. However, it should be noted that the computing device 300 in this specification may also include multiple processors, and thus operations of the method described in this specification that are performed by one processor may also be performed by multiple processors in combination or individually. For example, if both operations a and B are performed in a processor of this specification of computing device 300, it should be understood that operations a and step B may also be performed by two different processors in computing device 300, either in combination or separately (e.g., a first processor performing operation a, a second processor performing operation B, or both a first and second processor performing operations a and B).

The memory 320 may store data/information obtained from the MRI scanner 110, the terminal 140, the storage device 130, and/or any other component of the MRI system 100. In some embodiments, memory 320 may store one or more programs and/or instructions to perform the example methods described in this specification. For example, memory 320 may store a program for processing device 120 to perform SMS imaging.

I/O330 may input and/or output signals, data, information, and the like. In some embodiments, I/O330 may enable a user to interact with processing device 120. In some embodiments, I/O330 may include input devices and output devices. The input devices may include alphanumeric and other keys, and may be input via a keyboard, touch screen (e.g., with tactile or haptic feedback), voice input, eye-tracking input, brain-monitoring system, or any other similar input mechanism. Input information received via the input device may be sent via, for example, a bus to another component (e.g., processing device 120) for further processing.

The communication port 340 may be connected to a network (e.g., network 150) to facilitate data communication. The communication port 340 may establish a connection between the processing device 120 and the MRI scanner 110, the terminal 140, and/or the storage device 130.

Fig. 4 is a schematic diagram of exemplary hardware and/or software components of a mobile device 400 shown in accordance with some embodiments of the present description. In some embodiments, one or more components of the MRI system 100 (e.g., the terminal 140 and/or the processing device 120) may be implemented on the mobile device 400.

As shown in fig. 4, mobile device 400 may include a communication platform 410, a display 420, a Graphics Processing Unit (GPU) 430, a Central Processing Unit (CPU) 440, input/output 450, memory 460, and storage 490. In some embodiments, any other suitable component, including but not limited to a system bus or a controller (not shown), may also be included in mobile device 400. In some embodiments, an operating system 470 (e.g., ios, android, windows phone) and one or more application programs 480 may be loaded from storage 490 into memory 460 for execution by CPU 440. The application programs 480 may include a browser or any other suitable mobile application for receiving and presenting information related to the MRI system 100. User interaction with the information flow may be accomplished via the input/output 450 and provided to the processing device 120 and/or other components of the MRI system 100 via the network 150.

To implement the various modules, units, and their functions described in this specification, a computer hardware platform may be used as a hardware platform for one or more of the elements described herein. A computer with user interface elements may be used to implement a Personal Computer (PC) or any other type of workstation or terminal device. If programmed properly, the computer may also act as a server.

Fig. 5 is a block diagram of an exemplary processing device 120 shown in accordance with some embodiments of the present description. As shown in fig. 5, the processing device 120 may include a control module 501, an aliased image reconstruction module 502, a reference image generation module 503, a slice image reconstruction module 504, an acquisition module 505, and a quantitative measurement module 506.

The control module 501 may be configured to control one or more components of the MRI system 100. For example, during each of at least two (multiple) frames, the control module 501 may be configured to cause the MRI scanner to apply at least two (multiple) PE steps to each of at least two (multiple) layer locations of an object (e.g., a patient) to acquire a set of echo signals. As used herein, a layer position of an object may refer to a cross-section of the object parallel to an X-Y plane defined by coordinate system 160. A frame may refer to a time period of any duration. The PE step may refer to a single acquisition step for spatial encoding along the phase encoding direction. In some embodiments, during each of at least some of the PE steps in each frame, a phase modulation gradient may be applied along the slice encoding direction, for example, by a Z-coil of the MRI scanner. More description about the acquisition of echo signals may be found elsewhere in this specification. See, for example, step 601 in fig. 6 and its associated description.

The aliased image reconstruction module 502 may be configured to reconstruct an aliased image representing at least two (multiple) layer locations of an object in the frame based on a set of echo signals acquired in the frame. For example, the aliased image reconstruction module 502 may sample the echo signals acquired in the frame and store the sampled data in a k-space matrix. The aliased image reconstruction module 502 may further reconstruct the k-space matrix into aliased images of the frame by performing a fourier transform. More description about the reconstruction of aliased images may be found elsewhere in this specification. See, for example, step 602 in fig. 6 and its associated description.

The reference image generation module 503 may be configured to generate at least two reference layer images based on the at least two aliased images. A reference layer image refers to an image representing a layer position of at least two (or more) layer positions in one or more of at least two (or more) frames. In some embodiments, the reference layer image may be generated by combining (e.g., linearly combining) at least two of the aliased images of the frame. More description about the generation of the reference image may be found elsewhere in this specification. See, for example, step 603 in fig. 6 and its associated description.

The layer image reconstruction module 504 may be configured to reconstruct at least one layer image based on the aliased image and the reference layer image. Each layer in the at least one layer image may represent a layer position in one of the frames. In some embodiments, the at least one slice image may be reconstructed based on the aliased image and the reference slice image according to a parallel imaging reconstruction algorithm. More description about the reconstruction of the slice image may be found elsewhere in this specification. See, for example, step 604 in fig. 6 and its associated description.

The acquisition module 505 may be configured to acquire information related to the MRI system 100. For example, the acquisition module 505 may acquire at least two sets of undersampled k-space data corresponding to at least two frames (multiframes). Each set of undersampled k-space data may be acquired simultaneously from at least two (more) slice locations of the subject in one of at least two (multiple) frames using the MRI scanner. A set of undersampled k-space data corresponding to a frame may be acquired in the frame using an MRI scanner according to a sampling pattern (e.g., a pseudo-random sampling pattern). More description of acquiring undersampled k-space data may be found elsewhere in this specification. See, for example, step 1401 in fig. 14 and its associated description.

In some embodiments, the reference image generation module 503 may be further configured to reconstruct at least two reference layer images based on at least two sets of undersampled k-space data of at least two frames (multiframes). Each of the plurality of reference layer pictures may represent a layer position in the multi-frame. For example, the reference image generation module 503 may generate at least two sets of reference k-space data based on the undersampled k-space data and reconstruct at least two aliased images based on the reference k-space data. The reference image generation module 503 may further reconstruct the reference layer image based on the aliased image. More description about the generation of the reference layer image may be found elsewhere in this specification. See, for example, fig. 15 and its associated description.

The layer image reconstruction module 504 may be further configured to reconstruct at least two image sequence(s) based on the at least two sets of undersampled k-space data and the at least two reference layer images. Each of the at least two (plurality of) image sequences may correspond to one of the layer positions and comprise at least two layer images of the corresponding layer position in the frame. For example, the layer image reconstruction module 504 may estimate at least two reconstruction parameters (or parameters) based on the at least two reference layer images and reconstruct the image sequence by optimizing a cost function that includes at least some of the reconstruction parameters and at least two sets of undersampled k-space data. More description about the reconstruction of an image sequence can be found elsewhere in this specification. See, for example, step 1403 of FIG. 14 and its associated description.

In some embodiments, the acquisition module 505 may be configured to acquire at least two sets of k-space data corresponding to at least two (multiple) frames. Using the MRI scanner in one of at least two (multi) frames, each of at least two sets of K-space data are acquired simultaneously from at least two (multiple) slice positions of the subject, with a wait time after application of the preparation pulse in the frame. In some embodiments, phase modulation may be applied to at least two (or more) layer locations for interlayer separation in at least two (or more) frames. In some embodiments, the corresponding set of k-space data may be a set of fully sampled k-space data or a set of undersampled k-space data for each frame. More description about acquiring at least two sets of k-space data corresponding to at least two frames (multiframes) can be found elsewhere in this specification. See, for example, step 2101 and its associated description in FIG. 21.

The quantitative measurement module 506 may be configured to perform quantitative measurements on the object based on the at least two sets of k-space data acquired by the acquisition module 505. For example, the quantitative measurement module 506 may generate at least two quantitative maps of layer locations based on at least two sets of k-space data. The quantitative map of layer locations may comprise values of quantitative parameters for each physical point of a layer location. In some embodiments, at least two target slice images of a slice location may be generated along with a quantitative map of the slice location. The target layer image may be a layer image of a single layer location. Further description of the generation of at least two quantitative maps of layer positions may be found elsewhere in this specification. See, for example, step 2102 in FIG. 21 and associated description.

It should be noted that the foregoing description is for illustrative purposes only, and is not intended to limit the scope of the present disclosure. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. For example, processing device 120 may include one or more additional modules, such as a storage module (not shown) for storing data. As another example, one or more modules of the processing device 120 described above may be omitted. Additionally or alternatively, two or more modules of the processing device 120, such as the aliased image reconstruction module 502 and the reference image generation module 503, may be integrated into a single component. The modules of the processing device 120 may be divided into two or more units.

Fig. 6 is a flow chart of an exemplary process for multi-slice simultaneous MRI, shown in accordance with some embodiments of the present description. In some embodiments, the process 600 may be performed by the MRI system 100. For example, process 600 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, memory 320, and/or memory 490). In some embodiments, processing device 120 (e.g., processor 310 of computing device 300, CPU 440 of mobile device 400, and/or one or more modules shown in fig. 5) may execute the set of instructions and may be instructed accordingly to perform process 600.

In some embodiments, process 600 may be performed to simultaneously image at least two (multiple) layer locations of an object (e.g., a patient, a particular organ of a patient, a man-made object) using an MRI scanner. As used herein, a layer position of an object may refer to a cross-section of the object (e.g., a plane parallel to an X-Y plane defined by coordinate system 160). The count of imaging layer positions may be equal to any positive number, such as 2, 3, 4, 5, etc. The imaging layer position may be located anywhere on the subject. An MRI scanner performing simultaneous imaging may include one or more components similar to the MRI scanner 110 described in fig. 1 and 2. For example, an MRI scanner may include a main magnet, three sets of gradient coils, RF coils, etc., or any combination thereof. The three sets of gradient coils may be configured to generate gradient magnetic fields Gx, gy, and Gz in the X, Y, and Z directions, respectively, defined by coordinate system 160. For purposes of illustration, one of the at least two layer position(s) may be considered a first layer position, while the other layer position(s) may be considered at least one second layer position. The first layer position may be any layer position selected from at least two (or more) layer positions. In some embodiments, the first layer position may pass through the isocenter of the MRI scanner.

In 601, during each of at least two frames (multiframes), the processing device 120 (e.g., the control module 501, processing circuitry of the processor 310) may cause the MRI scanner to apply at least two PE step(s) to each of at least two layer position(s) of the object to acquire a set of echo signals.

As used herein, a frame may refer to a time period of any duration. The at least two frames (multiframes) may be continuous frames or discontinuous frames. Different frames may have the same duration or different durations. The PE step may refer to a single acquisition step for spatial encoding along the phase encoding direction. Each PE step in a frame may acquire echo signals from the excited layer location, where the acquired echo signals may be stored as PE lines in a single row of a k-space matrix corresponding to the frame. The k-space matrix corresponding to a frame may be a two-dimensional matrix having a Kx-axis along the frequency encoding direction and a Ky-axis along the phase encoding direction. The k-space matrix corresponding to the frame can be used to reconstruct an aliased image corresponding to the frame, as detailed in step 602.

In some embodiments, the matrix size of the k-space matrix corresponding to a particular frame may be associated with the resolution of the aliased image of the frame to be reconstructed. For example, to reconstruct an aliased image with a resolution of 256 × 128, it may be necessary to generate a 256 × 128k space matrix. That is, 256 PE steps may need to be applied in a particular frame to fill the 256 PE lines of the k-space matrix. The duration of a particular frame may be determined based on the count (or number) of PE steps and the unit duration of each PE step. In some embodiments, the k-space matrices corresponding to at least two (multiple) frames may have the same matrix size. PE lines located in the same row in the k-space matrix of different frames may be considered to be located at the same position in k-space. PE steps corresponding to PE lines located at the same position in k-space and applied to different frames may be considered to correspond to each other.

In some embodiments, during a frame, multiple PE steps may be performed by applying a particular pulse sequence. For example, a first pulse sequence without an echo sequence may be applied. The first pulse sequence may include at least two (more) RF excitation pulses, and only one echo signal (i.e., data corresponding to a single PE line) may be acquired after each RF excitation pulse. An exemplary first pulse sequence without an echo sequence may include a bSSFP and damaged GRE pulse sequence, among others. In some embodiments, each RF excitation pulse in the first pulse sequence may be a multiband RF pulse, which may be applied simultaneously with the slice selection gradient to simultaneously excite at least two (more) slice locations to be imaged.

As another example, a second pulse sequence with an echo sequence may be applied in a frame to perform the corresponding PE step. The second pulse sequence may acquire at least two (multiple) echo signals (i.e., data corresponding to at least two PE lines) after each single RF excitation pulse. An exemplary second pulse sequence with an echo sequence may include an EPI pulse sequence, an FSE pulse sequence, and the like. In some embodiments, different pulse sequences may be suitable for scanning different objects. For example, an EPI pulse sequence may be used to scan a patient's brain.

In 602, for each of at least two (or more) frames, processing device 120 (e.g., aliased image reconstruction module 502, processing circuitry of processor 310) may reconstruct an aliased image representing at least two (or more) layer locations in the frame based on a corresponding set of echo signals.

In some embodiments, for each frame, the processing device 120 may sample a set of echo signals acquired in the frame and store the sampled data in the k-space matrix corresponding to the frame as previously described. The processing device 120 may further reconstruct the k-space matrix corresponding to the frame as an aliased image of the frame by performing a fourier transform. The reconstructed aliased image may include aliasing artifacts, i.e. aliased pixels. In order to reduce aliasing artifacts in aliased images and to facilitate inter-layer separation based on aliased images, it may be desirable that in each reconstructed aliased image, the portions of the reconstructed aliased image that correspond to different layer positions of the object have a preset field of view (FOV) offset with respect to each other. For example, for an aliased image of two layer positions with a resolution of 128 × 128, it is desirable that the portions of the aliased image corresponding to the two layer positions have a half FOV offset from each other, for example, an offset of 64 pixels in the phase encoding direction. As another example, for an aliased image of three layer positions with a resolution of 128 × 300, it is desirable that the portions of the aliased image corresponding to each two adjacent layer positions have a one-third FOV offset from each other, e.g., an offset of 100 pixels in the phase encoding direction. In some embodiments, the preset FOV offset may be a default setting of the MRI system 100 or manually set by a user of the MRI system 100 via, for example, a terminal (e.g., terminal 140). Alternatively, the processing device 120 may determine the preset FOV offset based on, for example, a count of layer locations to be imaged, a distance between different layer locations, a sensitivity of an RF coil (e.g., RF coil 203) used for echo signal detection, or the like, or any combination thereof.

To achieve a preset FOV shift in the aliased image of the frame, at least two (multiple) phase modulation gradients may be applied by the gradient coils (e.g., Z-coils) of the MRI scanner along the slice encoding direction in the frame (i.e., the Z-direction of coordinate system 160). For example, during each PE step (or portion thereof) in a frame, a phase modulation gradient may be applied by the Z-coil of the MRI scanner along the slice encoding direction after excitation of the slice position and before readout of the corresponding echo signals. Due to the phase modulation gradient applied in the PE step, each layer position may have a specific phase when the corresponding echo signal is acquired.

In some embodiments, the phase modulation gradient applied in a frame may be designed to avoid the need for additional reference scans of layer position. For example, the phase difference between the second layer position and the first layer position is different for the corresponding PE step applied to a pair of frames of the at least two frames (multiframes), which may be two consecutive frames or non-consecutive frames of the at least two frames (multiframes). For example only, as shown in fig. 7, during each first PE step in frames 1 and 2, a phase modulation gradient may be applied such that the phase difference between layer positions S1 and S2 changes from-90 ° in frame 1 to 90 ° in frame 2. As another example, as shown in fig. 11, a phase modulation gradient may be applied during the first PE step in frame 3 such that the phase difference between layer positions S3 and S4 changes from-120 ° in frame 3 to 0 ° in frame 4, and the phase difference between layer positions S3 and S5 changes from-240 ° in frame 3 to 0 ° in frame 4.

In some embodiments, during at least one PE step in at least one frame, after readout of the respective echo signals, a compensating magnetic field gradient may be applied along the slice encoding direction. The compensation magnetic field gradient may have the same magnitude and an opposite gradient direction as the phase modulation gradient applied at the at least one PE step. This may eliminate or reduce the influence of the phase modulation gradient applied in the at least one PE step on the echo signal acquisition in the next PE step. In some embodiments, in each PE step of applying a phase modulation gradient, a compensation magnetic field gradient may be applied after reading out the corresponding echo signal. For example, during a frame in which the bSSFP pulse sequence is applied, a compensating magnetic field gradient may be applied in each PE step in the frame. Alternatively, the PE step in a frame in which the corrupted GRE pulse sequence is applied, for example, can be performed without compensating for the magnetic field gradient.

In some embodiments, a phase modulated RF excitation pulse may be applied in at least one PE step in at least one frame to excite at least two layer location(s), and phase modulation in the at least one PE step may be achieved by a combination of the phase modulated RF excitation pulse and a phase modulation gradient applied to the at least one PE step. For example, to achieve a 180 degree phase difference between the second layer position and the first layer position in the PE step, a 90 degree phase difference may be achieved by phase modulating the RF excitation pulses, and the remaining 90 degree phase difference is achieved by a phase modulating gradient. More description about the configuration of the pulse sequence applied in a frame can be found elsewhere in this specification. See, for example, fig. 7-14 and their associated description.

In 603, processing device 120 (e.g., reference image generation module 503, processing circuitry of processor 310) may generate at least two reference layer images based on the at least two (or more) aliased images.

As used herein, the term "a" or "an" refers to, a reference layer image refers to an image representing one of at least two (multiple) layer positions in one or more of at least two (multiple) frames. The temporal resolution of the reference layer image may be lower than the aliased image reconstructed in 602 and the layer image reconstructed in 604. For example, the aliased image may correspond to a single frame, while the reference layer image may be generated based on multiple aliased images, thereby having a lower temporal resolution.

In some embodiments, the reference layer image may be generated by combining (e.g., linearly combining) at least two (more) of the aliased images reconstructed in 602. For example, four aliased images (including the first, second, third, and fourth aliased images) corresponding to four frames (including the first, second, third, and fourth frames) may be reconstructed at 602. The reference layer image for a particular layer position may be generated by combining at least two (or more) aliased images of the four aliased images. For example only, the reference layer image R1 for the first layer location may be generated by superimposing the first and second aliased images or subtracting the first aliased image from the second aliased image. The reference layer image R1 may correspond to the first frame and the second frame, and has a lower temporal resolution than the original four aliased images. As another example, the reference layer image R2 of the first layer position may be a weighted sum of the first, second, and third aliased images. The reference layer image R2 may correspond to the first, second, and third frames and have a lower temporal resolution than the original four aliased images. In some embodiments, the average of the reference layer pictures R1 and R2 may be determined as the final reference layer picture for the first layer position.

In 604, the processing device 120 (e.g., layer image reconstruction module 504, processing circuitry of the processor 310) may reconstruct at least one layer image based on the aliased image and the reference layer image. Each of the at least one layer image may represent one of the at least two (or more) layer positions in one of the at least two (or more) frames. At least one layer of the image may have the same temporal resolution as the aliased image described at 602. As used herein, "based on an aliased image and a reference layer image" refers to "based on at least a portion of an aliased image and at least a portion of a reference layer image.

Reconstruction of the at least one layer of images may be performed according to a parallel imaging reconstruction algorithm (e.g., a slice-general auto-calibration partial parallel acquisition (GRAPPA) algorithm, a spatial harmonic acquisition (SMASH) algorithm, a sensitivity encoding (SENSE) algorithm, etc.) and based on aliased images and reference layer images. In some embodiments, for each layer position in each frame, a corresponding layer image may be reconstructed in 604. For example only, if there are two layer locations and two frames, four layer images may be reconstructed. Alternatively, only a portion of the four slice images may be reconstructed at 604. For example only, at 604, a slice image at a first slice position in a frame may be reconstructed based on the aliased image and the reference slice image at the first slice position in the frame according to the GRAPPA algorithm.

In some embodiments, the subject may experience physiological motion during at least the frame. For example, the object may comprise a heart of a patient undergoing cardiac motion. At least two (multiple) slice locations in the patient's heart may be imaged to generate a series of slice images for each slice location in at least two (multiple) cardiac phases. For a slice position in the heart of the patient, the corresponding slice image can dynamically show the heart movement of the slice position in the time dimension at different heart phases. In some embodiments, the subject may experience little or no physiological motion during at least two (or more) frames. For example, the object may comprise the brain of a patient. At least two (multiple) slice locations in the patient's brain may be imaged to generate a series of slice images for each slice location. For a layer location in the patient's brain, the corresponding layer image may dynamically account for changes in the activation region in the brain (e.g., changes in blood flow).

It should be noted that the above description of process 600 is for illustrative purposes only and is not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. In some embodiments, process 600 may be accomplished with one or more additional steps not described and/or omitting one or more of the steps described above. For example, the process 600 may include the additional step of sending the layer image to a terminal device (e.g., the doctor's terminal device 140) for display. In some embodiments, two or more steps of process 600 may be integrated into a single step, and/or a single step of process 600 may be split into two steps. For example only, steps 602 through 604 may be integrated into a single step, wherein processing device 120 may reconstruct a layer image based on at least two sets of echo signals acquired in 601. In some embodiments, a single reference layer image for a particular layer location may be generated in 603 to reconstruct the layer image for the particular layer location in 604.

Fig. 7 is a schematic diagram of an exemplary bSSFP pulse sequence 700 shown in accordance with some embodiments of the present description. The bSSFP pulse sequence 700 may be applied by an MRI scanner (e.g., the MRI scanner 110) to simultaneously image a layer location S1 and a layer location S2 of an object. As shown in fig. 7, the bSSFP pulse sequence 700 may be applied in frame 1 and frame 2 with different modulation schemes. During each of frames 1 and 2, at least two (multiple) PE steps (e.g., PE1, PE2, PE3, and PE4 as shown in fig. 7) may be applied to layer locations S1 and S2 to obtain a corresponding set of echo signals.

For purposes of illustration, the application of the bSSFP pulse sequence 700 in frame 1 is described below as an example. In each PE step in frame 1, an excitation RF pulse (e.g., a multiband RF pulse) may be applied simultaneously with the slice selection gradient to simultaneously excite layer locations S1 and S2, and echo signals may be acquired from layer locations S1 and S2. The echo signals acquired in each PE step in frame 1 may be stored as PE lines in the k-space matrix corresponding to frame 1. The aliased image A1 corresponding to layer positions S1 and S2 of frame 1 may be reconstructed by fourier transforming the k-space matrix corresponding to frame 1.

In some embodiments, during each PE step in frame 1, after excitation of the layer positions S1 and S2 and before readout of the respective echo signals, a phase modulation gradient may be applied by the Z-coil of the MRI scanner in order to impart a preset FOV/2 shift between the portions corresponding to the layer positions S1 and S2 in the aliased image A1. For example, the layer position S1 may be located at the isocenter of the MRI scanner, and the phase of the layer position S1 in the different PE steps in frame 1 may always be equal to 0 °. Due to the phase modulation gradient applied in the PE step in frame 1, the phase of the layer position S2 may alternate between-90 ° and 90 ° in the phase encoding direction, and the phase difference between the layer positions S1 and S2 may alternate between 90 ° and-90 ° in the phase encoding direction. In some embodiments, the strength of the phase modulation gradient applied in the PE step may be determined according to a preset FOV shift, a distance between the layer positions S1 and S2, a gyromagnetic ratio of the object, an amplitude of the phase modulation gradient, a duration of the phase modulation gradient, or the like, or any combination thereof. For example, the minimum value of the gradient moment Mz of the phase modulation gradient may be equal to φ/γ d, where φ refers to the phase difference between layer positions S1 and S2 introduced by the phase modulation gradient, γ refers to the gyromagnetic ratio, and d refers to the distance between layer positions S1 and S2.

Ideally, in the PE step in frame 1, the phase modulation of the layer positions S1 and S2 can be adjusted to 0 after readout of the respective echo signals and before the next excitation of the layer positions S1 and S2, in order to eliminate or reduce the influence of the phase modulation gradient on the echo signal acquisition in the next PE step. To this end, in some embodiments, after readout of the respective echo signals, a compensating magnetic field gradient (or so-called pre-phase gradient lobe) may be applied in the layer encoding direction in the PE step in frame 1 to keep the overall gradient balance, i.e. without net zero moment (net zero moment). The compensation magnetic field gradient applied in the PE step may have a phase modulation gradient with that applied in the PE step(s) ((s)) or called rephasing gradient lobes) of the same magnitude and with opposite gradient directions. For example, in a particular PE step in frame 1, the phase of layer location S2 is equal to-90 ° after applying the phase modulation gradient. After readout of the respective echo signals and before application of the next excitation radio frequency pulse, a compensation magnetic field gradient may be applied to change the phase of the layer position S2 by 90 ° to reach 0 °.

The application of the bsfp pulse sequence 700 in frame 2 may be similar to the application of the bsfp pulse sequence 700 in frame 1, except that the phase modulation gradient applied in each PE step of frame 2 may be different such that the phase difference between layer positions S1 and S2 is different for the corresponding PE steps in frames 1 and 2. For example only, as shown in FIG. 7, the phase of the layer location S2 in frame 2 may alternate between 90 and-90 along the phase encoding direction, and the phase difference between the layer locations S1 and S2 in frame 2 may alternate between-90 and 90 along the phase encoding direction. For the PE steps corresponding to PE lines at the same position in k-space and applied in frame 1 and frame 2, the phase difference between the layer positions S1 and S2 may vary by 180 °. Taking the first PE step applied in frame 1 and frame 2 as an example, the phase difference between the layer positions S1 and S2 changes from-90 ° in frame 1 to 90 ° in frame 2.

In some embodiments, processing device 120 may reconstruct an aliased image A1 corresponding to layer locations S1 and S2 of frame 1 based on the echo signals acquired in frame 1 and an aliased image A2 corresponding to layer locations S1 and S2 of frame 2 based on the echo signals acquired in frame 2 by performing, for example, step 602. Due to the phase modulation in frame 1 and frame 2, the aliased image A1 can be regarded as the sum of the layer positions S1 and S2, and the aliased image A2 can be regarded as the difference between the layer positions S1 and S2. The aliased images A1 and A2 may be represented by equation (1) and equation (2), respectively, as follows:

A1＝S1+S1, (1)

A2＝S1-S2. (2)

the reference layer image F1 representing the layer position S1 in the frame 1 and the frame 2 and the reference layer image F2 representing the layer position S2 in the frame 1 and the frame 2 can be determined by linearly combining the aliased images A1 and A2 according to equations (3) and (4), respectively, as follows:

the temporal resolution of the reference layer images F1 and F2 may be lower than the aliased images A1 and A2. The processing device 120 may also reconstruct one or more layer images of the layer positions S1 and S2 based on the aliased images A1 and A2 and the reference layer images F1 and F2. For example, the processing device 120 may reconstruct a layer image for each of the layer positions S1 and S2 in the frame 1 using a parallel imaging reconstruction algorithm based on the aliased image A1, the reference layer image F1, and the reference layer image F2. Similarly, the processing device 120 can reconstruct a layer image of each of the layer positions S1 and S2 in the frame 2 based on the aliased image A2, the reference layer image F1, and the reference layer image F2.

In some embodiments, the bSSFP pulse sequence 700 shown in fig. 7 may be applied to layer locations S1 and S2 in a patient' S heart for SMS cardiac MRI. For purposes of illustration, fig. 8A is an exemplary aliased image 810 of layer locations S1 and S2 in the heart acquired in frame 1, shown in accordance with some embodiments of the present description. FIG. 8B is an exemplary aliased image 820 of layer locations S1 and S2 in the heart acquired in frame 2, shown in accordance with some embodiments of the present description. Fig. 9A is an exemplary reference layer image 910 for layer position S1 in frames 1 and 2 shown according to some embodiments of the present description. Fig. 9B is an exemplary reference layer image 920 of layer position S2 in frames 1 and 2 shown according to some embodiments of the present description. Fig. 10 is an exemplary layer image 1010 of a layer location S1 in frame 1, an exemplary layer image 1020 of a layer location S2 in frame 1, an exemplary layer image 1030 of a layer location S1 in frame 2, and an exemplary layer image 1040 of a layer location S2 in frame 2, shown in accordance with some embodiments of the present description.

Fig. 11 is a schematic diagram of an exemplary bSSFP pulse sequence 1100 shown in accordance with some embodiments of the present description. The bSSFP pulse sequence 1100 may be applied by an MRI scanner (e.g., the MRI scanner 110) to simultaneously image slice locations S3, S4, and S5. As shown in fig. 11, the bSSFP pulse sequence 1100 may be applied in frame 3, frame 4, and frame 5 with different modulation schemes. It should be noted that the terms "layer location Sn" and "frame n" are used herein for convenience of description, and not for limitation. For example, frame 3 may be the same or different frame as frame 1 described in fig. 7. As another example, the tier location S3 may be the same or a different tier location than the tier location S1 described in fig. 7.

The application of the bSSFP pulse sequence 1100 in a frame may be similar to the application of the bSSFP pulse sequence 700 described in FIG. 7 in a frame, except that the phase modulation applied to the bSSFP pulse sequence 1100 may be different than the phase modulation of the bSSFP pulse sequence 700. Taking frame 3 as an example, after excitation of layer positions S3, S4 and S5 and before readout of the respective echo signals, a phase modulation gradient may be applied in each of the first PE step, the third PE step, the fourth PE step, the sixth PE step, etc. Due to the applied phase modulation gradient in frame 3, the phase of layer position S4 may periodically change from-120 ° to 0 ° to 120 ° in the phase encoding direction, and the phase difference between layer positions S3 and S4 may periodically change from-120 ° to 0 ° to 120 ° in the phase encoding direction in frame 3. The phase of the layer position S5 may be periodically changed from-240 deg. to 0 deg. to 240 deg. in the phase encoding direction, and the phase difference between the layer positions S3 and S5 may periodically vary from-240 deg. to 0 deg. and then to 240 deg. in the phase encoding direction in frame 3. The phase modulation gradient applied in frame 3 may impart a preset FOV/3 offset between adjacent layers in an aliased image A3 corresponding to frame 3, the aliased image A3 being reconstructed based on the signal acquired in frame 3.

The application of the bSSFP pulse sequence 1100 in frames 4 and 5 may be similar to the application of the bSSFP pulse sequence 1100 in frame 3, except that the phase modulation gradients applied in the three frames may be different from each other. Thus, the phase difference between layer positions S3 and S4 may be different and/or the phase difference between layer positions S3 and S5 may be different for the corresponding PE steps in a pair of frames 3, 4 and 5. For example only, the phase difference between S3 and S4 in the first PE step in frame 3 may be equal to-120 °, which becomes 0 ° in the first PE step in frame 4 and 120 ° in the first PE step in frame 5. As another example, the phase difference between S3 and S5 in the first PE step in frame 3 may be equal to-240 °, which becomes 0 ° in the first PE step of frame 4, and 240 ° in the first step of frame 5.

In some embodiments, processing device 120 may reconstruct an aliased image A3 corresponding to layer positions S3, S4, and S5 of frame 3 based on the echo signals acquired in frame 3, reconstruct an aliased image A4 corresponding to layer positions S3, S4, and S5 of frame 4 based on the echo signals acquired in frame 4, and reconstruct an aliased image A5 corresponding to layer positions S3, S4, and S5 of frame 5 based on the echo signals acquired in frame 5. Due to the phase modulation in frames 3, 4, and 5, aliased images A3, A4, and A5 may be represented by equation (5), equation (6), and equation (7), respectively, as follows:

A3＝S3+S4+S5, (5)

the reference layer image F3 representing the layer position S3 in the frames 3 to 5, the reference layer image F4 representing the layer position S4 in the frames 3 to 5, and the reference layer image F5 representing the layer position S5 in the frames 3 to 5 can be determined by linearly combining the aliased images A3, A4, and A5 according to equations (8), (9), and (10), respectively, as follows:

the reference layer images F3, F4, and F5 may have a lower temporal resolution than the aliased images A3, A4, and A5. The processing device 120 may also reconstruct one or more layer images of the layer positions S3, S4, and S5 based on the aliased images A3 to A5 and the reference layer images F3 to F5. For example, the processing device 120 may reconstruct a layer image for each of the layer positions S3, S4, and S5 in the frame 3 based on the aliased image A3 and the reference layer images F3, F4, and F5.

Fig. 12 is a schematic diagram of an exemplary FSE pulse sequence 1200, shown in accordance with some embodiments of the present description. The FSE pulse sequence 1200 may be applied by an MRI scanner (e.g., MRI scanner 110) to simultaneously image layer position S6 and layer position S7 of the subject. As shown in fig. 12, the FSE pulse sequence 1200 may be applied in frame 6 and frame 7 with different modulation schemes. During each frame in frame 6 and frame 7, a series of 180 ° echo pulses may be used after a single RF excitation pulse to perform multiple PE steps and acquire a corresponding sequence of echo signals.

Similar to the bSSFP pulse sequence 700 described in connection with fig. 7, a phase modulation gradient may be applied during each PE step of frames 6 and 7 such that the phase difference between layer positions S6 and S7 varies by 180 ° in the corresponding PE step in frames 6 and 7, as shown in fig. 12. After reading the respective echo signals and before the next PE step, it may be necessary to apply a compensating magnetic field gradient in each PE step of frame 6 and 7. In some embodiments, the processing device 120 may reconstruct one or more slice images of the slice locations S6 and S7 based on the echo signals acquired in the 6 th and 7 th frames. The reconstruction of the slice images at slice positions S6 and S7 may be performed in a manner similar to the reconstruction of the slice images at slice positions S1 and S2 described in fig. 7, and will not be described herein again.

Fig. 13 is a schematic diagram of an exemplary EPI pulse sequence 1300 shown in accordance with some embodiments of the present description. The EPI pulse sequence 1300 may be applied by an MRI scanner (e.g., MRI scanner 110) to simultaneously image layer position S8 and layer position S9 of the subject. As shown in fig. 13, EPI pulse sequence 1300 may be applied in frame 8 and frame 9 with different modulation schemes. During each frame in frame 8 and frame 9, a rephasing gradient can be used after a single RF excitation pulse to acquire multiple echoes for different PE steps.

Similar to the bSSFP pulse sequence 700 described in fig. 7, a phase modulation gradient may be applied during each PE step in frames 8 and 9 such that the phase difference between layer positions S8 and S9 varies by 180 ° in the corresponding PE step in frames 8 and 9, as shown in fig. 13. After reading the respective echo signals and before the next PE step, it may be necessary to apply a compensating magnetic field gradient in each PE step in frames 8 and 9. In some embodiments, the processing device 120 may reconstruct one or more slice images of the slice locations S8 and S9 based on the echo signals acquired in the 8 th and 9 th frames. The reconstruction of the slice images at slice positions S8 and S9 may be performed in a manner similar to the reconstruction of the slice images at slice positions S1 and S2 described in fig. 7, and will not be described herein again.

It should be noted that the exemplary pulse sequences and their descriptions as shown in fig. 7, 11, 12, and 13 are for illustrative purposes only and are not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. In some embodiments, the phase of a particular layer location in a particular PE step may be modulated to a value other than any other value shown in the figure. Furthermore, the phase modulation in a particular PE step may be achieved by the phase modulation gradient described above alone or by a combination of the phase modulation gradient and the phase modulated RF excitation pulse described above. Further, the equations provided above are illustrative examples and may be modified in various ways. For example, at least two aliased images of at least two frames (multiframes) may be reconstructed, and a reference layer image of a particular layer position may be generated based on any two or more of the at least two aliased images.

Fig. 14 is a flow diagram illustrating an exemplary process for multi-slice simultaneous MRI according to some embodiments of the present description. In some embodiments, process 1400 may be performed by MRI system 100. For example, process 1400 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, memory 320, and/or memory 490). In some embodiments, processing device 120 (e.g., processor 310 of computing device 300, CPU 440 of mobile device 400, and/or one or more modules shown in fig. 5) may execute the set of instructions and may be instructed accordingly to perform process 1400.

In 1401, the processing device 120 (e.g., the acquisition module 505, interface circuitry of the processor 310) may acquire at least two sets of undersampled k-space data corresponding to at least two (multiple) frames.

Each of the at least two sets of undersampled k-space data may be acquired simultaneously from at least two (more) slice locations of the subject in one of at least two (more) frames using an MRI scanner (e.g., MRI scanner 110). As illustrated in fig. 6, the layer position of the object refers to a cross section of the object. A frame refers to a time period of any duration.

In some embodiments, a set of undersampled k-space data may be acquired by instructing an MRI scanner to MR scan an object (e.g., a patient or a portion thereof). The MR scan may comprise at least two frames (multiframes). During each of at least two (multi) frames, the MRI scanner may be instructed to apply a plurality of PE steps to at least two (multiple) layer locations to acquire a set of echo signals, and each acquired echo signal may be stored as a PE line in a single row of the k-space matrix corresponding to the frame. In general, it may be desirable to acquire full k-space data of a layer position in a frame to reconstruct a full MR image corresponding to the layer position of the frame. To speed up data acquisition and reduce scan time, undersampling may be performed to acquire portions of full k-space data (i.e., a set of undersampled k-space data corresponding to the frame), using techniques such as reducing the number (or count) of k-space sampling steps, reducing the number (or count) of samples per row, reducing the number of lines per leaf (e.g., a set of parallel EP lines), reducing the number (or count) of leaves per acquisition, or the like, or any combination thereof. In some embodiments, a set of undersampled k-space data may be pre-acquired and stored in a storage device (e.g., storage device 130, memory 320, memory 490, and/or an external storage device). The processing device 120 may access the storage device and acquire a set of undersampled k-space data. Alternatively, the processing device 120 may acquire information related to a set of echo signals acquired in a frame from a storage device and generate a set of undersampled k-space data for the frame based on the acquired information.

In some embodiments, depending on the sampling mode, an MRI scanner may be used to collect a set of undersampled k-space data in a frame corresponding to the frame. The sampling pattern may specify a sampling trajectory along which a plurality of sampling points (forming one or more PE lines) are collected in a frame. Sampling patterns corresponding to different frames may be the same or different. In some embodiments, a random sampling pattern, such as a pseudo-random sampling pattern, may be employed in at least one of the at least two (or more) frames. The pseudo-random sampling pattern may be used to randomly acquire PE lines in at least one frame. Alternatively, at least two (a plurality of) pseudo-random values may be generated according to a pseudo-random sampling pattern, the pseudo-random values being distributed according to a given probability distribution, and PE lines corresponding to the pseudo-random values may be acquired. For example, the pseudo-random sampling pattern may be designed according to the Latin hypercube algorithm.

In some embodiments, the corresponding sampling patterns may be different and/or staggered for a pair of adjacent frames of the at least two (multi) frames. For example, a first sampling pattern to acquire odd PE lines may be employed in each odd frame, and a second sampling pattern to acquire even PE lines may be employed in each even frame. In some embodiments, the matrix-form k-space data of a frame (or simply k-space matrix) may be divided into multiple regions having the same sampling density (measured by, for example, a count of sampling points in a unit region) or different sampling densities. For example, k-space data may be fully sampled in one or more particular regions (e.g., the central region of the k-space matrix), while k-space data may be undersampled in other regions. Alternatively, the sampling density of one or more particular regions may be higher than the sampling density of other regions.

In some embodiments, to enable auto-calibrated multiband imaging, the phase of at least one of the layer positions may be modulated during scanning of the object. For example only, the layer locations to be simultaneously imaged may include a first layer location and at least one second layer location. During each frame (or portion thereof), a first layer location may be scanned without phase modulation and at least one second layer location (or portion thereof) may be scanned with phase modulation. The phase modulation of the second layer position in the frame may comprise phase modulation along a spatial dimension and/or phase modulation along a temporal dimension.

As used herein, the spatial dimension refers to the phase encoding dimension in k-space. Applying a phase modulation at a second layer location along a spatial dimension in a frame refers to modulating the phase of the second layer location during each PE step (or portion thereof) of the frame such that the phase of the second layer location varies along a phase encoding direction in the frame. In some embodiments, the phase of the second layer location may be modulated in the frame along the spatial dimension according to a phase modulation mechanism of the frame prior to acquiring the set of undersampled k-space data corresponding to the frame. The phase modulation mechanism of the frame may specify how the phase of the second layer location is modulated along the phase encoding dimension during the frame. For example, referring to fig. 13, the phase of layer location S9 may be modulated during each PE step in frame 8 according to a particular phase modulation scheme, and alternate between-90 ° and 90 ° along the phase encoding direction.

In some embodiments, for the second layer position, the phase modulation mechanism of the frame may be specifically designed such that a preset FOV shift is achieved between the portions corresponding to the second layer position and the first layer position in the reconstructed aliased image of the frame. For example, in a frame, the phase of the first layer position may always be equal to 0 °, and the phase of the second layer position may alternate between 0 ° and 180 ° in the phase encoding direction, thereby achieving a preset FOV/2 shift between the portions corresponding to layer positions S' and S in the aliased image. In some embodiments, the mechanism of phase modulation of the second layer position in the frame may be implemented by various phase modulation techniques described elsewhere in this specification (e.g., step 602 and its associated description), such as phase-modulated RF excitation pulses, magnetic field gradients (e.g., phase-modulated gradients along the layer encoding direction), compensating magnetic field gradients, and the like, or any combination thereof.

In some embodiments, the phase of the second layer position may be modulated along the time dimension such that the phase modulation mechanism of a pair of adjacent frames of the at least two (multi) frames is different. For example, the pair of adjacent frames may include a first frame and a second frame subsequent to the first frame. Due to the phase modulation along the time dimension, different phase modulation schemes may be applied in the first and second frames such that the phase of the second layer position changes from the first frame to the second frame by a global phase offset in the corresponding PE steps applied in the first and second frames. The global phase offset refers to a phase difference of the second layer position between corresponding PE steps applied in the pair of adjacent frames. The global phase offset may be equal to any positive value in the range of 0 ° to 360 °. The global phase offsets for different second layer locations may be the same or different.

In some embodiments, the at least two (plurality of) layer locations may include N layer locations, and the global phase offset may be (360/N) degrees. N may be a positive integer. For example, N may be equal to 2, i.e. two layer positions are scanned simultaneously in a frame, and the global phase offset may be 180 °. Referring to fig. 13, in frame 8, the phase of layer position S9 may be modulated in the spatial dimension according to a first phase modulation scheme and alternate between-90 ° and 90 °. The phase of the layer position S9 is also modulated in the time dimension, which results in a second phase modulation scheme corresponding to the frame 9 being different from the first phase modulation scheme. According to a second phase modulation scheme, the phase of the layer position S9 alternates between 90 ° and-90 ° along the spatial dimension in the frame 9. In the corresponding PE steps applied in frames 8 and 9, the phase of the layer position S9 is varied by 180 °, i.e. the global phase shift of the layer position S9 is 180 °. For another example, referring to fig. 11, in the corresponding PE steps of frames 3 and 4, the layer position S4 varies by 120 °, i.e., the global phase offset of the layer position S4 is 120 °; in the corresponding PE steps of frames 3 and 4, the layer position S5 is varied by 240 °, i.e. the global phase shift of the layer position S5 is 240 °.

It should be noted that the above description of phase modulation of at least one layer location is provided for illustrative purposes only, and is not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. For example, the phase of each slice position (including the first and second slice positions) may be modulated during the MR scan. As another example, the phase of the layer positions may be modulated in one of a spatial dimension and a temporal dimension. However, such changes and modifications do not depart from the scope of the present specification.

In some embodiments, phase modulation applied to simultaneously excited layer locations (or a portion thereof) may allow self-calibrating multiband imaging, i.e., a single-band reference layer image may be extracted from the undersampled set of k-space data itself, without the need for an additional reference scan. Furthermore, by using compressive sensing techniques to acquire undersampled k-space data, rather than fully sampled k-space data, the scanning process can be further accelerated.

At 1402, the processing device 120 (e.g., reference image generation module 503, processing circuitry of processor 310) may reconstruct at least two reference layer images based on the set of undersampled k-space data for at least two (or more) frames.

Each of the at least two reference layer pictures may represent a layer position in at least two (frames). The reference layer image may be unaliased and have a lower temporal resolution than the layer image generated in step 1403, since it is generated based on undersampled k-space data of at least two (multiple) frames. In some embodiments, processing device 120 may perform one or more steps of process 1500 as described in fig. 15 to reconstruct a reference layer image.

In 1403, the processing device 120 (e.g., the layer image generation module 504, the processing circuitry of the processor 310) may reconstruct at least two image sequence(s) based on the set of undersampled k-space data and the at least two reference layer images.

Each of the image sequences may correspond to one of the layer locations and may include at least two lines of layer images of the corresponding layer location in the frame. For example, a patient's cardiac cycle may include 12 cardiac phases, and layer positions a and B in the patient's heart may be imaged simultaneously using atmics as described above. An MR scan may include 12 or more frames (frames) covering 12 cardiac phases of the patient. Based on the undersampled k-space data acquired in the scan, an image sequence 2010 of layer positions a and an image sequence 2020 of layer positions B are generated as shown in fig. 20. Each of the image sequences 2010 and 2020 includes 12 slice images of 12 cardiac phases corresponding to a respective slice position. The temporal resolution of the image sequences 2010 and 2020 is equal to 2.88 × 15 milliseconds (ms), i.e., 43.2 ms. There are no significant artifacts in the image sequences 2010 and 2020, and the cardiac motion of the layer positions a and B in the cardiac cycle is dynamically displayed by the image sequences 2010 and 2020.

In some embodiments, to reconstruct the image sequence, the processing device 120 may estimate a plurality of reconstruction parameters based on the at least two reference layer images. For example, the MRI scanner may comprise at least two (multiple) receive coils for echo signal detection, and the reconstruction parameters may comprise at least two (multiple) coil sensitivity maps of the receive coils. In some embodiments, at least two coil images may be generated based on the at least two reference layer images, wherein each coil corresponds to a single receive coil. The coil images may be combined into a combined image according to, for example, a sum of squares (SOS) algorithm or an Adaptive Coil Combination (ACC) algorithm. The coil sensitivity maps for a particular receive coil may be determined by dividing the respective coil image by the combined image. In some embodiments, for each of the at least two reference layer images, a set of coil sensitivity maps may be determined based on the reference layer images, thereby generating multiple sets of coil sensitivity maps corresponding to different reference layer images (i.e., different layer locations).

After estimating the reconstruction parameters, the processing device 120 may reconstruct the image sequence by optimizing a cost function, wherein the cost function may include at least some reconstruction parameters and a set of undersampled k-space data. Optionally, the cost function may further comprise a temporal total variation operator related to a difference between images, the images corresponding to adjacent frames in each of the image sequences. In some embodiments, the first set of undersampled k-space data of the first frame may include some k-space data that is not included in the second set of undersampled k-space data of the second frame adjacent to the first frame. For example, the first set of undersampled k-space data may include odd PE lines, while the second set of undersampled k-space data may include even PE lines. The temporal total variation operator T may encourage information sharing between the first and second sets of undersampled k-space data in the reconstruction of the image sequence. For example, the temporal fully-variant operator T may fill the empty odd PE lines of the second set of undersampled k-space data with odd PE lines of the first set of undersampled k-space data. In some embodiments, the temporal total-variation operator T may be used to apply a sparse transform for L1 regularization. The sparse transformation may be performed based on one or more sparse transformation algorithms (e.g., wavelet (WT) algorithm, cosine (CT) algorithm, contour (contourlet) algorithm, curvelet (curvelet) algorithm, k-means singular value decomposition (k-means singular value decomposition) algorithm, gabor algorithm, etc.), or any combination thereof.

For the purpose of illustration, it is assumed that the layer positions to be imaged simultaneously comprise two layer positions (i.e. one first layer position and one second layer position), the image sequence x used for reconstructing the first layer position ₁ And a sequence x of images at a second layer position ₂ An exemplary cost function (11) of (a) is as follows:

wherein s is ₁ Refers to a coil sensitivity map, s, determined based on a reference layer image of the first layer position ₂ A coil sensitivity map determined based on a reference layer image of a second layer position, D a k-space sampling operator, F a Fourier transform operator, p ₁ Means for phase modulation with respect to the position of the first layer in the frame, p ₂ Refers to the phase modulation scheme with respect to the second layer position in the frame, and λ refers to the indication | Tx ₁ ‖ ¹ And | Tx ₂ ‖ ¹ And T refers to the time total variation operator. Tx ₁ Possibly and with the image sequence x ₁ The difference between the corresponding layer images of the adjacent frames is correlated. Tx ₂ Possibly and with the image sequence x ₂ The difference between the corresponding layer images of the adjacent frames is correlated. Minimizing x of a cost function (e.g., the cost function shown in equation (11)) ₁ And x ₂ Can be used as a sequence of images of the first and second layer positions.

It should be noted that the cost function (11) shown above is for illustrative purposes only and is not intended to limit the scope of the present description. For example, the cost function (11) may comprise one or more additional parameters. Additionally or alternatively, one or more parameters of the cost function (11), such as λ | Tx ₁ ‖ ¹ And/or λ | Tx ₂ ‖ ¹ And may be omitted.

It should be noted that the above description of process 1400 is for illustrative purposes only and is not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. In some embodiments, process 1400 may be accomplished with one or more additional steps not described and/or omitting one or more of the steps described above. For example, the process 1400 may include the additional step of sending at least two (multiple) image sequences to a terminal device for diagnosis (e.g., the physician's terminal device 140).

FIG. 15 is a flow diagram of an exemplary process for reconstructing at least two reference layer images, according to some embodiments of the present description. In some embodiments, one or more steps of process 1500 may be performed to implement at least a portion of step 1402 as described in fig. 14.

In 1501, the processing device 120 (e.g., the reference image generation module 503, the processing circuitry of the processor 310) may generate at least two sets of reference k-space data based on a set of undersampled k-space data corresponding to a frame.

In some embodiments, the processing device 120 may generate a set of reference k-space data by combining (e.g., linearly combining) undersampled k-space data corresponding to two or more frames. For example, a frame may include one or more odd frames and one or more even frames. The sets of reference k-space data may comprise a first set of reference k-space data corresponding to odd frames and a second set of reference k-space data corresponding to even frames. The processing device 120 may generate a first set of reference k-space data based on one or more sets of undersampled k-space data corresponding to odd frames and a second set of reference k-space data based on one or more sets of undersampled k-space data corresponding to even frames. In some embodiments, the first set of reference k-space data may be determined by averaging the set of undersampled k-space data corresponding to the odd frame. Additionally or alternatively, the second set of reference k-space data may be determined by averaging the set of undersampled k-space data corresponding to the even frames.

At 1502, the processing device 120 (e.g., reference image generation module 503, processing circuitry of processor 310) may reconstruct at least two aliased images based on at least two sets of reference k-space data. Each of the at least two aliased images may represent at least two (multiple) layer positions in more than one of the at least two (multiple) frames.

In some embodiments, the processing device 120 may reconstruct at least two aliased images by fourier transforming at least two sets of reference k-space data. For example, the processing device 120 may reconstruct aliased images corresponding to odd frames from the first set of reference k-space data and aliased images corresponding to even frames from the second set of reference k-space data.

In 1503, the processing device 120 (e.g., reference image generation module 503, processing circuitry of processor 310) may generate at least two reference layer images based on the at least two aliased images.

In some embodiments, step 1503 may be performed in a manner similar to step 603. For example, the processing device 120 may generate a reference layer image by combining (e.g., linearly combining) at least two aliased images (or a portion thereof) reconstructed in 1502.

It should be noted that the above description of process 1500 is for illustrative purposes only and is not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. In some embodiments, process 1500 may be accomplished with one or more additional steps not described and/or omitting one or more of the steps described above. Additionally or alternatively, two or more steps (e.g., steps 1501 and 1502) may be integrated into a single step.

Fig. 16 is a schematic diagram of an exemplary phase modulation and undersampling pattern 1600 in an MR scan, shown in accordance with some embodiments of the present description. An MR scan may be performed to simultaneously image a first slice position and a second slice position of the object. As shown in fig. 16, the MR scan may include at least two (multiple) odd frames and at least two (multiple) even frames. A random undersampling pattern is used in each of the at least two odd frame(s) and the at least two even frame(s). The circle and cross icons in fig. 16 may represent a 180 ° phase difference and a 0 ° phase difference between the first layer position and the second layer position, respectively. In each odd frame, the odd PE lines may have a 180 ° phase difference between the first layer position and the second layer position, and the even PE lines may have a 0 ° phase difference between the first layer position and the second layer position. In each even frame, the odd PE lines may have a 0 ° phase difference between the first layer position and the second layer position, and the even PE lines may have a 180 ° phase difference between the first layer position and the second layer position.

In some embodiments, after acquiring a set of undersampled k-space data according to the phase modulation and undersampling mode 1600, a single band reference layer image of the first layer location and the second layer location may be generated based on the set of undersampled k-space data, e.g., performing the exemplary process shown in fig. 17. As shown in fig. 17, a first set of reference K-space data K1 corresponding to an odd frame may be determined based on the set of undersampled K-space data corresponding to the odd frame; and, a second set of reference K-space data K2 corresponding to the even frame may be determined based on the set of undersampled K-space data corresponding to the even frame. The first set of reference K-space data K1 may then be reconstructed into an aliased image A1' representing the first layer position and the second layer position in the odd frame. Due to the phase modulation applied to the odd frame, the aliased image A1' can be considered as the sum of the first and second layer positions. Similarly, a second set of reference K-space data K2 can be reconstructed into an aliased image A2' representing the first and second layer positions in the even frame. Due to the phase modulation applied to the even frame, the aliased image A2' can be considered as the difference between the first and second layer positions. Further, a reference layer image F1 'representing the first layer position and a reference layer image F2' representing the second layer position can be determined by linearly combining the aliased images A1 'and A2'. The generation of the reference layer images F1 'and F2' may be performed in a manner similar to the generation of the reference layer images F1 and F2 as described in fig. 7, and will not be described herein again.

Fig. 18 is an illustration of an exemplary phase modulation mechanism for a first layer position and a second layer position in a frame, in accordance with some embodiments of the present description. As shown in fig. 18, the phase of the first layer position in the different PE steps is always equal to 0 °, and the phase of the second layer position is alongThe phase encoding direction is modulated. The phase difference between the first layer position and the second layer position is equal to during each odd PE step

And in each even PE step equals

In each PE step, the phase of the second layer position is modulated by a phase modulation gradient 1801 (or rephasing gradient lobe) before the readout of the respective echo signal, and the total gradient of the second layer position is balanced by a compensating magnetic field gradient 1802 (or prephase gradient lobe) after the readout of the respective echo signal and before the next PE step. It should be understood that the phase modulation mechanism in fig. 18 is provided for illustrative purposes only and is not intended to be limiting. Various modifications may be made to the phase modulation mechanism. For example, the first layer position may also be phase modulated in the frame. As another example, in a part of the PE step, the phase modulation of the second layer position may be omitted. As yet another example, the compensating magnetic field gradient 1802 may be omitted.

Fig. 19 is layer images 1910, 1920, 1930, and 1940 shown corresponding to the same cardiac phase of a patient according to some embodiments of the present description. The layer images 1910 and 1920 correspond to one layer location of the patient's heart and the layer images 1930 and 1940 correspond to another layer location of the patient's heart. The patient is scanned using a compressed sensing technique while the slice images 1910 and 1930 are acquired. The patient is scanned while the slice images 1920 and 1940 are acquired by using the ATOMICS technique disclosed in this specification (e.g., according to process 1400). The heart morphology is described in each of the slice images 1910 to 1940. Compared with the compressed sensing technology only, the ATOMICS technology combines the multi-band imaging technology with automatic calibration and the compressed sensing technology, and can accelerate the scanning process without affecting the image quality.

FIG. 21 is a flow diagram of an exemplary process for generating at least two quantitative maps of at least two layer location(s) according to some embodiments of the present description. In some embodiments, process 2100 may be performed by MRI system 100. For example, process 2100 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, memory 320, and/or memory 490). In some embodiments, processing device 120 (e.g., processor 310 of computing device 300, CPU 440 of mobile device 400, and/or one or more modules shown in fig. 5) may execute the set of instructions and may be instructed accordingly to perform process 2100.

In 2101, the processing device 120 (e.g., the acquisition module 505) may acquire at least two sets of k-space data.

The at least two sets of k-space data may correspond to at least two frames (multiframes). The MRI scanner may be used in one of at least two frames (multiframes) with each of at least two sets of k-space data acquired simultaneously from at least two slice positions (multiple slices) of the subject, with a latency after application of the preparation pulse. In other words, the processing device 120 may acquire at least two sets of k-space data for at least two (multiple) slice positions using SMS imaging. SMS imaging may include at least two frames (multiframes). Each of the at least two sets of k-space data may correspond to a latency of a preparation pulse applied to the at least two (multiple) layer positions during SMS imaging. As illustrated in fig. 6, the layer position of the object refers to a cross section of the object, and the frame refers to a period of time having any duration.

For example only, in a frame, a preparation pulse may be applied to a layer location of an object, followed by a certain latency. After the waiting time, pulse sequences may be applied to the layer positions simultaneously to implement at least two (multiple) PE steps and to acquire a corresponding set of k-space data. The preparation pulse may be used to acquire data for quantitative measurement of layer position. The quantitative measurements may be used to determine one or more quantitative parameters of the layer position, such as T1, T2, transverse relaxation decay (T2), signal decay rate (R2), transverse relaxation rate (R2), etc., or any combination thereof. For example, to make a T1 measurement at a layer location, a T1 preparation pulse (e.g., IR pulse) may be used. As another example, to make a T2 measurement at a layer location, a T2 preparation pulse may be used.

The latency of a frame refers to the time period between the preparation pulse and the first excitation pulse in the pulse sequence for performing the PE step during the frame. For example, in T1 imaging, the waiting time may also be referred to as the inversion Time (TI) between the IR pulse and the 90-degree excitation pulse applied after the IR pulse. To achieve T1 measurement, the latency of at least two frames (multiframes) may be different. As used herein, the latency of at least two frames (multiframes) may be considered to be different if the latency of the at least two frames (multiframes) is partially or completely different.

In some embodiments, the latency in a frame may be related to the layer position to be imaged. For example, the reference T1 of the layer position may be estimated from the anatomy of the layer position. The TI value for at least two (or more) frames may be set manually by a user (e.g., a doctor) based on the reference T1 or automatically by a computer device (e.g., processing device 120). For example, the TI value for at least two frames (multiframes) may be 100 milliseconds (ms), 200 ms, 350 ms, and so on. The pulse sequence applied after the wait time may include a GRE pulse sequence, a FSE pulse sequence, an EPI pulse sequence, a bSSFP pulse sequence, or any other suitable pulse sequence (e.g., as described in fig. 2).

In some embodiments, during SMS imaging for interlayer separation, phase modulation may be applied to one or more targeted layer selection locations of at least two (or more) layer locations in a frame. As used herein, a target floor position may also be referred to as a second floor position. The target slice position may comprise all or a portion of the imaging layer position.

In some embodiments, for each target slice position in each frame, the phase of the target slice position may be modulated along a spatial dimension (i.e., a phase encoding dimension) according to a phase modulation mechanism of the frame. For example, during a frame, the phase of the target slice position may be modulated such that the target slice position has a different phase during readout of different PE lines. Phase modulation applied to the target slice position along the spatial dimension may be used in the reconstructed aliased image of the frame to achieve a preset FOV shift between portions corresponding to different slice positions.

Additionally or alternatively, for each target slice position, the phase of the target slice position may be modulated along the time dimension such that the phase modulation mechanism of a pair of adjacent frames of the at least two (multiple) frames is different. For example, a pair of adjacent frames may include a first frame and a second frame following the first frame. Due to the phase modulation along the time dimension, different phase modulation schemes may be applied in the first and second frames such that the phase of the target slice position varies from the first frame to the second frame by a global phase offset in the corresponding PE steps applied in the first and second frames. In some embodiments, the phase modulation mechanism of the target slice position in a third frame subsequent to the second frame may be different from the phase modulation mechanism in the second frame and the same as or different from the phase modulation mechanism in the first frame.

By way of example only, referring to fig. 23, in frame 10, the phase of layer location S11 is modulated in the spatial dimension according to a first phase modulation scheme and alternates between-90 ° and 90 °. The phase of the layer position S11 is also modulated in the time dimension, which results in a second phase modulation scheme corresponding to the frame 11 being different from the first phase modulation scheme. According to a second phase modulation scheme, the phase of the layer position S11 alternates between 90 ° and-90 ° along the spatial dimension in the frame 11. In the corresponding PE steps applied in frames 10 and 11, the phase of the layer position S11 is changed by 180 °, i.e. the global phase shift of the layer position S11 is 180 °. As another example, referring to fig. 24, the phase of the layer position S13 alternates between 180 ° and 0 ° along the spatial dimension in frame 12 and between 0 ° and 180 ° along the spatial dimension in frame 13. In the corresponding PE steps applied in frames 12 and 13, the phase of the layer position S13 is varied by 180 °, i.e. the global phase shift of the layer position S13 is 180 °.

In some embodiments, phase modulation of the target slice position may be achieved by various phase modulation techniques described elsewhere in this specification (e.g., steps 602 and 1401 and their associated description), such as phase-modulated radio frequency excitation pulses, magnetic field gradients (e.g., phase-modulated gradients along the slice encoding direction), compensating magnetic field gradients, and the like, or any combination thereof. In some embodiments, phase modulation applied to the target slice position can be used to enable auto-calibrated (or self-calibrated) multiband imaging, i.e., a single-band reference slice image can be extracted from a set of k-space data itself without additional reference scans. More description of the phase modulation applied to the target slice position may be found elsewhere in this specification. See, e.g., the description of phase modulation applied to the second layer locations as described in step 1401.

In some embodiments, for each frame, the corresponding set of k-space data may be a set of fully sampled k-space data acquired by full sampling. Alternatively, for each frame, the corresponding set of k-space data may be a set of undersampled k-space data acquired according to an undersampled mode in the frame. The sampling pattern corresponding to different frames may be the same or different. For example only, a pseudo-random sampling pattern may be employed in at least one of the at least two (or more) frames to randomly acquire PE lines in the at least one frame. In some embodiments, the undersampling patterns of a pair of adjacent frames of a frame may be different and/or interleaved. In some embodiments, after averaging the undersampled k-space data of at least two (or more) frames, one or more particular regions (e.g., a central region of k-space) may be fully sampled (or nearly fully sampled) in order to improve the accuracy of image reconstruction based on the undersampled k-space data. More description of the undersampling mode may be found elsewhere in this specification. See, for example, step 1401 and its associated description. The scanning process can be further accelerated by using a compressed sensing technique to acquire undersampled k-space data instead of fully sampled k-space data.

In 2102, the processing device 120 (e.g., quantitative measurement module 506) may generate at least two quantitative maps of at least two (multiple) slice positions based on at least two sets of k-space data.

As used herein, a quantitative map of a layer location may include values of quantitative parameters for each physical point of the layer location. Exemplary quantification maps for an object may include T1 maps, T2 maps, R2 maps, and the like, or any combination thereof.

In some embodiments, at least two target layer images for at least two layer locations(s) may be generated together with at least two quantification maps for at least two layer locations(s). The target layer image may be a layer image of a single layer location. In some embodiments, the target layer image of a layer location may reflect the signal strength of each physical point of the layer location corresponding to the saturated magnetic moment. In some embodiments, the target layer images may have a temporal resolution above a threshold (e.g., a temporal resolution of the reference layer images as described elsewhere in this specification). In some embodiments, processing device 120 may simultaneously generate at least two quantitative maps of layer locations based on the set of k-space data by performing process 2200 as described in fig. 22.

The present specification provides systems and methods for improving the efficiency of quantitative measurements by incorporating SMS technology. In contrast to conventional techniques that separately measure multiple layer locations, the provided systems and methods may utilize SMS technology to simultaneously generate quantitative maps of multiple layer locations. Further, in some embodiments, the provided systems and methods can utilize a specially designed phase modulation mechanism to enable auto-calibrated multi-band imaging, and target slice images of slice positions can be generated along with quantitative maps of slice positions. In other words, interlayer separation is achieved by phase modulation without additional scanning for generating a reference layer image, which can improve scanning and reconstruction efficiency and avoid errors that may occur in additional scanning.

In some embodiments, phase modulation may be applied to one or more target slice positions of the at least two (or more) slice positions along the time dimension. Due to the phase modulation along the time dimension, differences between MRI signals of target slice locations acquired in different frames may be amplified and information of different slice locations may be more easily separated, which may improve the signal-to-noise ratio (SNR) of the generated quantitative map and the target slice image. Furthermore, in accordance with some embodiments of the present specification, compressed sensing techniques may be utilized and at least two sets of undersampled k-space data may be acquired according to one or more particular undersampled patterns in a frame. The use of compressed sensing techniques can further speed up the data acquisition process and shorten the scan time.

FIG. 22 is a flow diagram of an exemplary process for generating at least two quantitative maps of at least two layer locations, shown in accordance with some embodiments of the present description. In some embodiments, one or more steps of process 2200 may be performed to implement at least a portion of step 2102 as described in conjunction with fig. 21.

As depicted in step 2102, the quantification map may include a T1 map, a T2 map, a R2 map, the like, or any combination thereof. For illustrative purposes, the following description is made with reference to the generation of a T1 diagram of layer positions and is not intended to limit the scope of this specification.

In 2201, the processing device 120 (e.g., the quantitative measurement module 506) may determine one or more reconstruction parameters based on at least two sets of k-space data.

For example, the MRI scanner may comprise a plurality of receive coils for echo signal detection, and the reconstruction parameters may comprise at least two coil sensitivity maps of the receive coils. For SMS imaging, the reconstruction parameters may include at least two coil sensitivity maps for the receive coil for each slice location. In some embodiments, for each layer position, the processing device 120 may generate a reference layer image of the layer position based on at least two sets of k-space data. The processing device 120 may also determine at least two coil sensitivity maps corresponding to each layer position based on the reference layer image of the layer position. The coil sensitivity maps for each slice position may be specified as part of one or more reconstruction parameters. As described in step 603, the reference layer picture of a layer position refers to a picture representing a layer position in more than one frame of at least two frames (multiframes). The reference layer pictures may have a lower temporal resolution than the target layer pictures to be reconstructed in 2203. In some embodiments, for each layer position, the processing device 120 may generate at least two coil images of at least two (more) receive coils based on the reference layer image of the layer position, and then generate a coil sensitivity map for the layer position from the coil images. For example, a combined image of the coil images may be generated based on a sum of squares (SOS) algorithm, and the coil sensitivities of particular receive coils may be determined by dividing the respective coil images by the combined image.

In some embodiments, the at least two sets of k-space data may be at least two sets of fully sampled k-space data acquired in a frame. The processing device 120 can reconstruct an aliased image corresponding to each frame based on the corresponding set of fully-sampled k-space data and generate a reference layer image based on the aliased images of the frame (e.g., by combining two or more aliased images). More description on generating reference layer images based on fully sampled k-space data may be found elsewhere in this specification. See, for example, steps 602 and 603 and their associated description. In some embodiments, if the set of k-space data is at least two sets of undersampled k-space data acquired in a frame, the processing device 120 may generate a reference layer image based on the set of undersampled k-space data by performing step 1402 as described in fig. 14 or process 1500 as described in fig. 15.

At 2202, the processing device 120 (e.g., the quantitative measurement module 506) may construct an optimization function that includes at least two quantitative maps for at least two layer locations (or locations), at least two target layer images for at least two layer locations (or locations), one or more reconstruction parameters, and at least two sets of k-space data.

In some embodiments, the optimization function may be reconstructed based on a signal model that constructs a relationship between the latency and the quantitative parameters of at least two quantitative maps corresponding to at least two (multiple) layer positions. For the T1 plot, for example only, an optimization function may be constructed based on an inversion recovery signal model that constructs the relationship between TI and T1. For purposes of illustration, assuming that the layer locations to be imaged simultaneously include two layer locations (i.e., one first layer location and one second layer location), an exemplary optimization function (12) for T1 imaging is as follows:

where y denotes at least two sets of k-space data acquired in a frame, x ₁ ' target layer image indicating first layer position, T _{1_1} Graph T1, x representing the position of the first layer ₂ ' target layer image representing second layer position, T _{1_2} To representMap T1, s of second layer position ₁ Representing the coil sensitivity map, s, corresponding to the position of the first layer ₂ A coil sensitivity map corresponding to a second slice position is shown,

representing an inversion recovery signal model, D representing a k-space sampling operator, F representing a Fourier transform operator, p ₁ Indicating the phase modulation scheme applied to the position of the first layer in the frame, p ₂ Indicating the phase modulation scheme applied to the second layer position in the frame, λ ₁ Means indicating | T' x ₁ ′‖ ¹ Regularization parameter of importance, λ ₂ Indicating | T' x ₂ ′‖ ¹ The regularization parameter of importance, T', represents the spatial total variation operator.

In the optimization function (12), x ₁ ′、x ₂ ′、T _{1_1} And T _{1_2} May be an unknown factor to be resolved. In some embodiments, the spatial total-variation operator T' may reflect a spatial variation of pixel values (or voxel values) in the image, e.g., it may be associated with differences between pixel values of neighboring pixels or voxel values of neighboring voxels in the image. The spatial total-variation operator T' in the optimization function (12) can be used to impose a limit on the spatial variation of the pixel values (or voxel values) of the target layer image and make the target layer image smoother. In some embodiments, the target layer image x ₁ ' A signal intensity of each physical point of the first layer position corresponding to the saturation magnetic moment, the target layer image x ₂ ' may reflect the signal strength of each physical point of the second layer location corresponding to the saturated magnetic moment. In some embodiments, the inversion restores the signal model

Can be expressed in the following form:

where x denotes the target layer image at the layer position, T1 denotes the T1 plot of the layer position, TI denotes the inversion time, S0 denotes the layer position corresponding to the saturation momentThe signal strength. In some embodiments, the signal model is recovered in inversion

In (3), S0 may be replaced by x.

It should be noted that the optimization function (12) provided above is merely an example, and are not intended to be limiting. The optimization function (12) can be modified according to actual needs. For example, one or more coefficients may be omitted or replaced with other similar coefficients, and/or one or more additional coefficients may be added. For example only, the spatial total variation operator T' may be replaced by another sparse operator. Or, λ ₁ |T′x ₁ ′| ₁ And lambda ₂ |T′x ₂ ′| ₁ May be omitted. As another example, D may be omitted if the set of k-space data is fully sampled k-space data.

At 2203, the processing device 120 (e.g., the quantitative measurement module 506) may generate at least two quantitative maps of at least two (or more) layer locations by solving an optimization function.

In some embodiments, the target layer image for at least two (more) layer locations and the quantitative map for at least two (more) layer locations may also be generated simultaneously by solving the optimization function. For example, the target layer image x of the first layer position at which the optimization function (12) is minimized may be solved simultaneously ₁ ', target layer image x of second layer position ₂ ', T1 FIG. T of first layer position _{1_1} And a second layer position T1 map T _{1_2} . In some embodiments, after determining the T1 map and the target layer image of the layer location, the processing device 120 may restore the signal model from the inversion

A layer image of the layer position corresponding to any TI is generated. For example, the target layer image x can be obtained by ₁ ', T1 FIG. T _{1_1} And a specific TI is input to the inversion recovery signal model

Generating a first layer corresponding to a particular TILayer images of the locations. As another example, the target layer image x may be generated by dividing the target layer image x ₁ ', T1 FIG. T _{1_1} And TI corresponding to a specific frame is input to the inversion recovery signal model

A layer image corresponding to a first layer position of a particular frame is generated.

According to some embodiments of the present description, an optimization function may be constructed to simultaneously determine a target layer image and a quantitative map of multiple layer positions of an object. The efficiency of the quantitative measurement can be improved by using an optimization function. For example, with conventional T1 map techniques, multiple acquisitions with different TIs may be required at a single layer position to acquire multiple images corresponding to the multiple TIs, and the T1 map of the layer position may be determined by signal fitting. By using the optimization functions disclosed herein, the originally acquired k-space data corresponding to different TI (or frames) can be used, thereby avoiding the need for image reconstruction and signal fitting and saving computational resources (e.g., computational time and/or required memory space). Further, the optimization function can combine the quantitative maps of the multiple slice locations and the target slice image, such that multiple dimensions of information can be determined together by solving the optimization function. Further, an optimization function may be constructed based on the inversion recovery signal model, which may improve the signal-to-noise ratio of the generated T1 map.

It should be noted that the above description of process 2100 and process 2200 is for illustrative purposes only and is not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. In some embodiments, process 2100 and/or process 2200 may be accomplished with one or more additional steps not described and/or omitting one or more of the steps discussed above. For example, the process 2200 may include the additional step of sending the quantification map and the target layer image to a terminal device (e.g., the physician's terminal device 140) for display. In some embodiments, two or more steps, such as steps 2201 and 2202, may be integrated into a single step or performed in any order.

Fig. 23 is a schematic diagram of an exemplary pulse sequence shown in accordance with some embodiments of the present description. The T1 map and the target layer image for each of the layer positions S10 and S11 can be generated using a pulse sequence as shown in fig. 23. As shown in fig. 23, in frame 10, IR pulses may be applied to layer positions S10 and S11, and a GRE pulse sequence 2300 may be applied after a waiting time TI 1. In frame 11, IR pulses may be applied to layer positions S10 and S11, and a GRE pulse sequence 2300 may be applied after a wait time TI2. TI1 may be different from TI2. The GRE pulse sequence 2300 may be applied in frames 10 and 11 having different modulation schemes.

For purposes of illustration, the application of the GRE pulse sequence 2300 in the frame 10 will be described below as an example. In each PE step in frame 10, an excitation RF pulse (e.g., a multiband RF pulse) with a slice-select gradient may be applied to simultaneously excite layer locations S10 and S11, and echo signals may be acquired from layer locations S10 and S11. The echo signals acquired in each PE step in frame 10 may be stored as PE lines in a k-space matrix corresponding to frame 10.

To achieve auto-calibrated multiband imaging, a phase modulation gradient may be applied to the layer position S11 during each PE step of the frame 10, such that the phase of the layer position S11 may alternate between-90 ° and 90 ° along the spatial dimension (i.e., phase encoding direction) in the frame 10. Furthermore, the phase of the layer position S11 may be modulated in the time dimension. For example, as shown in fig. 23, the phase of layer location S11 may be varied by a global phase offset of 180 ° for the corresponding PE step in frames 10 and 11.

In some embodiments, due to the phase modulation applied to layer position S11, processing device 120 may generate reference layer images for layer positions S10 and S11 based on the echo signals acquired in frames 10 and 11 without additional reference scans of layer positions S10 and S11. The generation of the reference layer images at layer positions S10 and S11 may be performed in a manner similar to the generation of the reference layer images at layer positions S1 and S2 described in fig. 7, and will not be described again here. The reference layer image can also be used for quantitative measurements on the layer positions S10 and S11. For example, the processing device 120 may determine a set of coil sensitivity maps corresponding to the layer position S10 and a set of coil sensitivity maps corresponding to the layer position S11 based on the reference layer image. The processing device 120 may simultaneously generate a T1 map and a target layer image of the layer positions S10 and S11 by solving an optimization function (12) based on the k-space data acquired in the 10 th and 11 th frames, the coil sensitivity maps corresponding to the layer positions S10 and S11, and the phase modulation mechanism with respect to the layer positions S10 and S11.

Fig. 24 is a schematic diagram of an exemplary pulse sequence shown in accordance with some embodiments of the present description. The T1 map and the target layer image of each of the layer positions S12 and S13 of the subject can be generated using a pulse sequence as shown in fig. 24. As shown in fig. 24, in frame 12, IR pulses may be applied to layer positions S12 and S13, and FSE pulse sequence 2400 may be applied after wait time TI 3. In frame 13, IR pulses may be applied to layer positions S12 and S13, and the FSE pulse sequence 2400 may be applied after the wait time TI4. TI3 may be different from TI4. Like the layer position S11, the layer position S13 may be phase modulated in the spatial and temporal dimensions. Due to the phase modulation applied to the layer position S13, reference layer images of the layer positions S12 and S13 may be generated based on the echo signals acquired in the frames 12 and 13, and the reference layer images may further be used for quantitative measurements of the layer positions S12 and S13.

It should be noted that the exemplary pulse sequences and their descriptions described above in fig. 23 and 24 are provided for illustrative purposes only and are not intended to limit the scope of the present description. Many variations and modifications may be made by one of ordinary skill in the art in light of the teachings of this specification. However, such changes and modifications do not depart from the scope of the present specification. In some embodiments, the phase of a particular layer location in a particular PE step may be modulated to a value other than any other value shown in the figure. Furthermore, phase modulation in a particular PE step may be achieved by phase modulation gradients alone, phase modulation RF excitation pulses, or a combination thereof. Additionally or alternatively, a compensating magnetic field gradient may be applied in each PE step. Further, the count of frames may be equal to any positive number, e.g., 2, 3, 4, etc. For example, the processing device 120 may acquire k-space data corresponding to eight frames, and the TI values of the eight frames may be different.

Also, the description uses specific words to describe embodiments of the description. For example, "one embodiment," "an embodiment," and/or "some embodiments" means a certain feature, structure, or characteristic described in connection with at least one embodiment of the specification. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Similarly, it should be noted that in the foregoing description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, the inventive body should possess fewer features than the single embodiment described above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". For example, "about," "approximately," or "substantially" may indicate a variation of ± 1%, ± 5%, ± 10%, or ± 20% of the value they describe, unless otherwise specified. Accordingly, in some embodiments, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. It will thus be seen that the embodiments described herein, by way of example and not limitation, alternative configurations of the embodiments of the present specification may be considered consistent with the teachings of the present specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims (10)

1. A magnetic resonance imaging system comprising:

an acquisition module for acquiring at least two sets of K-space data corresponding to at least two frames, wherein each of the at least two sets of K-space data is acquired simultaneously from at least two slice positions of a subject using a magnetic resonance imaging scanner in one of the at least two frames, and there is a wait time after applying a preparation pulse in the frame; and

a quantitative measurement module for generating at least two quantitative maps of the at least two slice positions based on the at least two sets of k-space data, wherein

Applying phase modulation to at least one target layer position of the at least two layer positions for inter-layer separation in the at least two frames.

2. The system of claim 1, wherein for each of the at least one target layer location, the phase of the target layer location is modulated along a spatial dimension during each of the at least two frames according to a phase modulation mechanism of the frame.

3. The system of claim 2, wherein for each of the at least one target layer location, a phase of the target layer location is modulated along a time dimension such that a phase modulation mechanism of a pair of adjacent frames of the at least two frames is different.

4. The system of claim 1, wherein at least two target layer images for the at least two layer locations are generated together with at least two quantification maps for the at least two layer locations.

5. The system of claim 4, wherein said generating at least two quantitative maps of said at least two slice locations based on said at least two sets of k-space data comprises:

determining one or more reconstruction parameters based on the at least two sets of k-space data;

constructing an optimization function comprising at least two quantitative maps for the at least two slice positions, at least two target slice images for the at least two slice positions, the one or more reconstruction parameters, and the at least two sets of k-space data; and

and generating at least two quantitative graphs and at least two target layer images of the at least two layer positions by solving the optimization function.

6. The system of claim 5, wherein the optimization function is constructed based on a signal model that constructs a relationship between the latency and quantitative parameters of at least two quantitative maps corresponding to the at least two layer positions.

7. The system according to claim 5, wherein said determining one or more reconstruction parameters based on said at least two sets of k-space data comprises:

for each of the at least two layer locations, generating a reference layer image for the layer location based on the at least two sets of k-space data; and

at least two coil sensitivity maps corresponding to each of the at least two layer locations are used as part of the one or more reconstruction parameters based on the reference layer images of the at least two layer locations.

8. The system of claim 1, wherein for each of the at least two frames, the corresponding set of k-space data is a set of undersampled k-space data collected according to the intra-frame undersampling pattern.

9. The system of claim 8, wherein the undersampling patterns of a pair of adjacent frames of the at least two frames are interleaved.

10. A non-transitory computer readable medium comprising a set of instructions for image stitching, wherein the set of instructions, when executed by at least one processor, instruct the at least one processor to implement a method comprising:

acquiring at least two sets of K-space data corresponding to at least two frames, wherein each set of K-space data in the at least two sets of K-space data is acquired simultaneously from at least two slice locations of a subject using a magnetic resonance imaging scanner in one of the at least two frames, and there is a wait time after applying a preparation pulse in the frame; and

generating at least two quantification maps of the at least two layer positions based on the at least two sets of k-space data, wherein

Applying phase modulation to at least one target layer position of the at least two layer positions for inter-layer separation in the at least two frames.

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