JP6757200B2 - Diagnostic imaging device and magnetic resonance imaging device - Google Patents

Description

The present invention relates to an image diagnostic apparatus such as a magnetic resonance imaging (hereinafter referred to as "MRI") apparatus, and more particularly to a technique using compressed sensing for image reconstruction.

An image diagnostic device such as an MRI device or an X-ray CT device reconstructs an image of an inspection target by performing an operation on a plurality of signals obtained by measuring the inspection target. The larger the number of measurement data used for image reconstruction, the higher the spatial resolution and SN of an image can be obtained. However, in order to increase the number of measurement data, it is generally necessary to extend the measurement time or increase the number of measurements.

As a high-speed technique for shortening the measurement time, for example, in an MRI apparatus, various high-speed pulse sequences and parallel imaging using a plurality of receiving coils are known. On the other hand, it has been proposed to apply a compressed sensing technique for reconstructing an observation target from sparse information obtained from the observation target to an image diagnostic apparatus such as an MRI apparatus (Patent Documents 1, 2, etc.). In compressed sensing, when acquiring time-series data, the measurement is thinned out under specific conditions, and the image is reconstructed from the measured data in a short time by repeatedly performing calculations with a predetermined algorithm at the time of reconstruction.

U.S. Pat. No. 7,646,924 Japanese Unexamined Patent Publication No. 2015-205307

In the human body measurement targeted by the diagnostic imaging apparatus, the required measurement time, reconstruction time, and SN (signal-to-noise ratio) of the output image differ depending on the measurement target part and measurement conditions. Although Patent Document 1 and Patent Document 2 propose a thinning method and an objective function for iterative calculation, the application of compressed sensing technology according to a target site and measurement conditions is not considered.

Therefore, the present invention provides an image diagnostic device to which compressed sensing technology is applied, which can optimize the measurement time, reconstruction time, SN of the output image, etc. according to the target site and measurement conditions. The challenge is to provide.

In order to achieve the above object, the diagnostic imaging apparatus of the present invention has a relationship between the conditions related to compressed sensing (CS conditions) and the image conditions (for example, SN value) required according to the target site and measurement conditions. Based on this, it has means for setting the optimum CS conditions. Specifically, the diagnostic imaging apparatus of the present invention performs CS calculation based on compressed sensing using a measurement unit that acquires measurement data from an inspection target and sparse measurement data acquired by the measurement unit, and performs CS calculation on the inspection target. The storage unit includes a calculation unit that reconstructs the image of the image and a storage unit that stores data used for CS calculation of the calculation unit, and the storage unit uses the SN predicted value of the image and the compressed sensing conditions as the data. The calculation unit sets the conditions for compressed sensing using the designated measurement conditions and the relationship.

Further, the MRI apparatus of the present invention includes a measurement unit that collects a nuclear magnetic resonance signal from an inspection target and acquires k-space data, and a measurement control unit that controls the thinning rate of k-space data acquired by the measurement unit. A calculation unit that performs CS calculation based on compressed sensing and reconstructs an image using k-space data acquired at a predetermined thinning rate, and a storage unit that stores data used for CS calculation of the calculation unit are provided. The storage unit stores the relationship between the SN predicted value of the image and the compressed sensing condition as the data, and the computing unit uses the SN specified by the user and the relational expression to perform the compressed sensing. Set the conditions for.

According to the present invention, it is possible to determine the optimum thinning measurement / reconstruction time for a target portion and measurement conditions without increasing the burden on the user, and to realize image reconstruction to which compressed sensing is applied.

The block diagram which shows the outline of the diagnostic imaging apparatus which concerns on this invention. The figure which shows the whole outline of the MRI apparatus which concerns on this invention. It is a figure explaining the measurement pattern in the MRI apparatus, (a) is the figure which shows the measurement pattern of the Cartesian scan of k-space data, (b) is the figure which shows the measurement pattern of the radial scan. FIG. 6 is a flow chart of the process of the first embodiment. The figure which shows the SN value prediction formula used in Embodiment 1. A table showing the relationship between the inspection site and the measurement target and the desired SN used in the first embodiment. The figure explaining the CS condition setting in Embodiment 1. FIG. FIG. 6 is a flow chart of the process of the second embodiment. The graph which shows the desired SN for each cross-sectional position used in Embodiment 2. FIG. 6 is a flow chart of the process of the third embodiment. The figure explaining the CS condition setting in Embodiment 3. The figure which shows an example of the UI displayed on the display part of Embodiment 3. FIG. 6 is a flow chart of the process of the fourth embodiment. The figure explaining the CS condition setting in Embodiment 4. The figure which shows an example of the UI displayed on the display part of Embodiment 4.

Hereinafter, preferred embodiments of the diagnostic imaging apparatus of the present invention will be described with reference to the accompanying drawings.
<First Embodiment>
The diagnostic imaging apparatus of this embodiment will be described with reference to the block diagram shown in FIG.

The diagnostic imaging device 100 is a device that applies compression sensing to shorten the measurement time. The measurement unit 110 that acquires a signal from the measurement target and the measurement unit 110 use the signal obtained by the measurement target to measure the measurement target. A user interface for exchanging information and inputting commands between the arithmetic unit 120 that reconstructs an image, the operation of the measurement unit 110 and the arithmetic unit 120, the control unit 130, and the arithmetic unit 120 and the control unit 130. It includes 140 and a storage unit 150 that stores data, problems, and the like necessary for the operation of the calculation unit 120 and the control unit 130. Depending on the information to be stored, the storage unit 150 is constructed not only in the storage device provided in the diagnostic imaging device 100, but also in a portable storage medium, a remote storage device connected via the Internet, or a network cloud. It may include a database, a storage medium, and the like.

In the diagnostic imaging apparatus 100, the calculation unit 120 includes a CS calculation unit 121 in order to perform a CS calculation. The CS calculation unit 121 reconstructs the image to be measured based on the sparse measurement data according to a predetermined CS algorithm. Further, the control unit 130 sets the measurement control unit 131 for operating according to the operation procedure of the measurement unit 110, the pulse sequence in the case of an MRI device, and the CS conditions, and the measurement unit 110 and the CS calculation unit are set according to the set CS conditions. It includes a CS condition setting unit 132 that controls 121. The user interface 140 includes an input unit 141 including an input device for input by the user, and a display unit 142 for displaying an image, a GUI, etc. created by the calculation unit 120.

In the storage unit 150, a predetermined graph or table showing the relationship between the target site, the measurement purpose, or a combination thereof (collectively referred to as the measurement condition) and the CS condition is stored as the database 151. The measurement conditions include the target part, the SN required for the image, the imaging time, etc., and the CS conditions include conditions related to measurement such as thinning pattern, thinning rate at the time of measurement, and conditions related to calculation such as calculation time. Is included. Of the CS conditions, the thinning pattern and the thinning rate may be set as measurement conditions only for conditions related to calculation. Since the relationship between the measurement conditions and the CS conditions (graphs and tables) differs depending on the characteristics of the type of diagnostic imaging apparatus, it is necessary to acquire each type in advance and store it in the database 151.

The diagnostic imaging apparatus 100 performs imaging by applying compressed sensing under the control of the control unit 130. At that time, when the input of the measurement condition is received via the input unit 141, the optimum CS condition is set according to the measurement condition and the image is taken by using the relationship between the measurement condition stored in the storage unit 150 and the CS condition. I do. The CS condition can be set either manually or automatically. In the case of manual (arrow shown by the dotted line in FIG. 1), the information necessary for the user to select the CS condition, specifically, predetermined A graph or table showing the relationship between the measured measurement condition and the CS condition or a candidate for the CS condition derived from the graph or table is presented to the user. The user determines the CS condition based on the presented information and sets it via the input unit 141.

The functions of the calculation unit 120 and the control unit 130 shown in FIG. 1 are mainly realized by executing software provided in the diagnostic imaging apparatus 100 or incorporated in a general-purpose CPU. It is also possible to realize some or all of the functions with hardware such as ASIC and FPGA.

According to the diagnostic imaging apparatus of the present embodiment, the CS conditions can be optimized according to the target site and the measurement time. Specifically, the required measurement time, reconstruction time, and SN of the output image differ depending on the target site and measurement conditions. The measurement time differs depending on the thinning rate and the thinning pattern, and the reconstruction time and the SN of the output image differ depending on the thinning rate and the time required for the CS calculation (setting of the end condition of the CS calculation). The diagnostic imaging apparatus of the present embodiment is unnecessary by setting CS conditions suitable for the set target parts and measurement conditions based on a predetermined relationship between the target parts and measurement conditions and CS conditions. It is possible to prevent the CS calculation time from being extended.

This embodiment can be applied to a medical image diagnostic device such as a CT device that images a measurement target by using a plurality of time-series measurement data in addition to an MRI device.

<Second embodiment>
The present embodiment is an embodiment in which the present invention is applied to an MRI apparatus.
First, an overall overview of the MRI apparatus to which the present invention is applied will be described with reference to FIG. The MRI apparatus shown in FIG. 2 obtains a tomographic image of a subject by utilizing an NMR phenomenon, and includes a static magnetic field generating unit 2, a gradient magnetic field generating unit 3, a transmitting unit 5, a receiving unit 6, and signal processing. A unit 7, a sequencer 4, and a central processing unit (CPU) 8 are provided. The static magnetic field generating unit 2, the gradient magnetic field generating unit 3, the transmitting unit 5, and the receiving unit 6 are collectively referred to as a measuring unit.

The static magnetic field generator 2 is composed of a permanent magnet type, a normal conduction type or a superconducting type static magnetic field generation source. Depending on the direction of the static magnetic field, there are a perpendicular magnetic field method and a horizontal magnetic field method. In the vertical magnetic field method, the direction perpendicular to the body axis of the subject 1 in the space where the subject 1 is placed, and in the horizontal magnetic field method, the body axis direction. Each generates a uniform static magnetic field.

The gradient magnetic field generating unit 3 includes a gradient magnetic field coil 9 wound in the three axial directions of X, Y, and Z, which is a coordinate system (static coordinate system) of the MRI apparatus, and a gradient magnetic field power supply 10 for driving each gradient magnetic field coil. By driving the gradient magnetic field power supply 10 of each coil in accordance with a command from the sequencer 4 described later, the gradient magnetic fields Gx, Gy, and Gz are applied in the three axial directions of X, Y, and Z. A gradient magnetic field can be generated in any direction by combining these three axial directions, and at the time of imaging, a slice direction gradient magnetic field pulse (Gs) is applied in a direction orthogonal to the slice plane (imaging cross section) with respect to the subject 1. A slice plane is set, and a phase encode direction gradient magnetic field pulse (Gp) and a frequency encode direction gradient magnetic field pulse (Gf) are applied to the echo signal in the remaining two directions orthogonal to the slice plane and orthogonal to each other. Encode the position information in each direction.

The sequencer 4 is a control means that repeatedly applies a high-frequency magnetic field pulse (hereinafter referred to as “RF pulse”) and a gradient magnetic field pulse in a predetermined pulse sequence, operates under the control of the CPU 8, and collects tomographic image data of the subject 1. Sends various commands necessary for the measurement unit. The function of the sequencer 4 and the CPU 8 that controls the sequencer 4 is called a measurement control unit. Various pulse sequences are prepared in advance according to the imaging target and the imaging purpose, and the sequencer 4 calculates and executes the pulse sequence when a predetermined pulse sequence and imaging parameters are determined. In this embodiment, compressed sensing is adopted, and the imaging parameters include not only imaging parameters such as general echo time TE, repetition time TR, and flip angle FA, but also data thinning rate.

The transmission unit 5 irradiates the subject 1 with an RF pulse in order to cause nuclear magnetic resonance in the nuclear spins of the atoms constituting the biological tissue of the subject 1. The high-frequency oscillator 11, the modulator 12, and the high-frequency amplifier It is composed of 13 and a high frequency coil (transmission coil) 14a on the transmission side. The high-frequency pulse output from the high-frequency oscillator 11 is amplitude-modulated by the modulator 12 at the timing commanded by the sequencer 4, and the amplitude-modulated high-frequency pulse is amplified by the high-frequency amplifier 13 and then placed close to the subject 1. By supplying the high frequency coil 14a, an RF pulse is applied to the subject 1.

The receiving unit 6 detects an echo signal (NMR signal) emitted by nuclear magnetic resonance of the nuclear spins constituting the biological tissue of the subject 1, and is a high-frequency coil (reception coil) 14b and a signal amplifier 15 on the receiving side. It is composed of an orthogonal phase detector 16 and an A / D converter 17. The NMR signal of the response of the subject 1 induced by the electromagnetic wave emitted from the high frequency coil 14a on the transmitting side is detected by the high frequency coil 14b arranged close to the subject 1, amplified by the signal amplifier 15, and then amplified. At the timing according to the command from the sequencer 4, the orthogonal phase detector 16 divides the signals into two orthogonal systems, each of which is converted into a digital quantity by the A / D converter 17 and sent to the signal processing unit 7.

The signal processing unit 7 performs various data processing, displays and saves processing results, and functions as a calculation unit and a control unit, and includes a CPU 8, an external storage device such as an optical disk 19, a magnetic disk 18, and a display 20. , It has an internal storage device such as ROM 21 and RAM 22, and an operation unit 25. When the data from the receiving unit 6 is input to the CPU 8, the CPU 8 executes processing such as signal processing and image reconstruction, and displays the tomographic image of the subject 1 as a result on the display 200 and an external storage device. For example, it is recorded on a magnetic disk 18 or the like.

The operation unit 25 inputs various control information of the MRI apparatus and control information of the processing performed by the signal processing unit 7, and includes a trackball or a mouse 23, a keyboard 24, and the like. The operation unit 25 is arranged close to or integrally with the display 20, and the user interactively controls various processes of the MRI apparatus through the operation unit 25 while looking at the display 20.

The MRI apparatus of the present embodiment incorporates compressed sensing technology, and has a function of determining the condition (CS condition), particularly controlling the measuring unit and the arithmetic unit according to the determined CS condition to perform the measurement and calculation of the compressed sensing. It is equipped with a function to adjust the condition (CS condition) according to the measurement site and measurement purpose, and a function to perform compressed sensing calculation (CS calculation).

Here, the compressed sensing applied to the MRI apparatus will be described with reference to FIG. FIG. 3 is a diagram showing k-space data. Here, data in the slice direction is omitted, and 2D k-space data in which the phase encoding direction is vertical and the frequency encoding direction is horizontal is shown. There are several different methods for collecting k-space data. FIG. 3 (a) shows a Cartesian scan (raster scan) that collects data parallel to the ky axis in k-space, and FIG. 3 (b) shows k. It shows a radial scan that collects data radially around the origin of space. In general imaging, the data that fills all the grids in the k-space is arranged and the image is reconstructed. In compressed sensing, the radiation density is set to a smaller number of samplings than general imaging, and k-space data with missing data, that is, sparse measurement data is obtained (undersampling). The data collection method for obtaining sparse measurement data is not limited to the Cartesian scan and the radial scan, and may be a spiral scan for acquiring k-space data in a spiral shape. When the sparse measurement data is random, a better approximation can be made, and such a thinning pattern is introduced in, for example, Patent Document 1.

Further, as a technique for performing sparse measurement in a radial scan, for example, a method of measuring a plurality of radiation data while taking an angle of time-adjacent radiations to an angle called a golden angle (GA) is known. There is. In GA, even if the number of radiations increases, the radiations do not overlap with the radiations acquired before that, and are randomly arranged, resulting in random and sparse k-space data. The thinning rate is, for example, the ratio (%) of the number of radiations when sparse measurement data is obtained, assuming that the number of radiations used in general imaging is 100 in a radial scan.

The signal processing unit 7 (calculation unit) reconstructs an image by a compressed sensing algorithm using such undersampled k-space data. The compressed sensing algorithm is stored as a program in the storage device of the MRI apparatus. Alternatively, the arithmetic unit uploads a program stored in another storage device. The compressed sensing algorithm solves optimization problems such as L1 norm minimization by iterative algorithm after sparse conversion of the measured data. Wavelet transform, a combination of it and Curvelet transform, TV (Total) Variation), Ridgelet transform, etc. Such compressed sensing algorithms are known and are available as software packages such as, for example, L1-SPIRiT, L1-ESPRIRiT, SAKE-L1ESPRIRiT, and TVG (Total Generic Variation: an improved version of TV). Most of these compressed sensings are combined with parallel imaging operations that assume the use of a plurality of receiving coils, and the above-mentioned sparse measurement in this embodiment is also sparse using a plurality of receiving coils. It may be a measurement.

The compressed sensing operation ends when the iterative algorithm included in the operation satisfies a predetermined end condition, and the solution obtained at that time is used as image data. The end condition includes a predetermined threshold (weak threshold), a threshold for the number of repetitions, a calculation time, and the like. In the present embodiment, this end condition is appropriately controlled according to the measurement condition.

The functions related to compressed sensing described above are mainly realized by the signal processing unit 7. Specifically, the signal processing unit 7 is provided with software that functions as a CS calculation unit 121 and a CS condition setting unit 132 as shown in FIG. 1, and a storage unit including an external storage device and the like is provided. Stores a database of predetermined relational expressions and tables.

Hereinafter, a specific embodiment of setting the CS condition will be described with reference to the functional block diagram of FIG.
<< CS Control Embodiment 1 >>
In the present embodiment, the control unit 130 performs imaging by applying CS using a table showing the relational expression between the repetition condition of the CS calculation and the expected SN and the relationship between the measurement condition and the required SN.

Hereinafter, the processing procedure of the present embodiment will be described using the flow shown in FIG.
First, when the user specifies measurement conditions including a predetermined thinning pattern and thinning rate via the operation unit 25, the measurement control unit starts thinning measurement according to the set pulse sequence and the specified measurement conditions. (S401). In parallel with the measurement, the CS condition setting 132 reads the expected SN value equation 410 under the specified measurement condition from the storage device (S402). The measurement conditions include, for example, an examination site and imaging conditions of blood vessel imaging or parenchymal imaging. The predicted SN value formula 410 is, for example, as shown in FIG. 5, a plot of the predicted SN value with respect to the calculation time of the CS operation under this measurement condition, and may be a graph or a fitting function of the graph. Good. Such a calculation formula can be obtained in advance if the algorithm of the CS calculation to be used, the data collection method handled by the algorithm, and the amount of data are known, and is stored in the storage unit (database A) 150.

Next, the CS condition setting unit 132 acquires the required SN value 420 for each inspection site and measurement condition stored in the storage unit (database B) 150 (S403). The required SN value 420 for each inspection site and measurement condition is, for example, a table as shown in FIG. 6, and the required SN value may be a relative (qualitative) regulation as shown in the figure or defined as a numerical range. It may be the one that was done.

The CS condition setting unit 132 repeats the CN calculation that satisfies the required SN value under the specified inspection site and measurement conditions based on the expected SN value formula 410 acquired in S401 and the required SN value 420 acquired in S402. Conditions, such as repetition time or number of repetitions, are determined (S404). For example, in the case of an inspection site such as the head having a high required SN value, the repetition time is maximized within the time allowed for calculation. On the other hand, in the case of imaging the liver parenchyma, the repetition time is shortened. FIG. 7 shows an example of setting the CS repetition condition based on the required SN value. Depending on the algorithm of CS calculation, the end condition may be determined by the threshold value, but since the high and low of the threshold value correspond to the length of the repetition time, the threshold value should be determined in conjunction with the determination of the repetition time. Can be done.

The CS calculation unit 121 starts the reconstruction by the CS algorithm using the data (k-space data) thinned out by S401 (S405). Then, the CS calculation unit 121 ends the calculation with the repetition time set in S403 or the threshold value derived from the repetition time as the end condition of the calculation (S406).

According to the present embodiment, since the CS calculation end condition is set so as to satisfy the required SN value depending on the part, the image can be reconstructed and presented without spending more time on the CS calculation than necessary. ..

<< CS Control Embodiment 2 >>
The present embodiment is characterized in that, in addition to the CS control of the first embodiment, the CS condition satisfying the required SN value is set in consideration of the position of the imaging cross section.
Hereinafter, the processing procedure of the present embodiment will be described using the flow shown in FIG. In FIG. 8, the same processing as the flow of FIG. 4 used in the first embodiment is indicated by the same reference numerals, and detailed description thereof will be omitted.

After acquiring the expected SN value formula 410 under each imaging condition and the required SN value 420 at each inspection site (S401 to S403), the CS condition setting unit 132 is required at each position of the imaging cross section as shown in FIG. The SN value 430 is acquired from the storage unit (database C) (S411). As shown in FIG. 9, when acquiring 3D data of the inspection site, the required SN value is not always the same depending on the position of the cross section. For example, the most important diagnostic region is imaged so as to be located in the center of the imaging target region, and the highest SN value is required in the cross section located in the center. The CS condition setting unit 132 sets the end condition of the iterative calculation for each cross section based on the required SN value of each cross section (S412).

After that, performing the CS calculation (S405, S406) is the same as in the first embodiment.
According to this embodiment, the entire calculation time can be optimized in more detail by setting the end condition for each CS calculation of each cross section.

<< CS Control Embodiment 3 >>
The present embodiment is characterized in that, in addition to the CS control of the first embodiment, a function of presenting a candidate for CS condition to the user and allowing the user to select the candidate is added.
Hereinafter, the processing procedure of the present embodiment will be described using the flow shown in FIG. In FIG. 10, the same processing as the flow of FIG. 4 used in the first embodiment is indicated by the same reference numerals, and detailed description thereof will be omitted.

The CS condition setting unit 132 acquires the expected SN value formula 410 under each measurement condition and the required SN value 420 at each inspection site (S401 to S403). The CS condition setting unit 132 determines the repetition condition using the expected SN value formula 410 and the required SN value 420, and presents the determined repetition condition and the SN value obtained at that time to the user, for example, displaying it on the display unit 142. (S421). If the user determines that there is no problem with the SN value of the presented repetition condition (S422), the CS calculation is started with the determined repetition as in the first embodiment (S405). When the user desires an SN value higher or lower than the presented SN value (S422), the CS condition setting unit 132 repeats a plurality of repetitions based on the expected SN value formula 410 and the required SN value for the inspection site. Candidates for the end condition are determined (S423), and the expected reconstruction time for each candidate is determined (S424). As shown in FIG. 11, the candidate is, for example, one or a plurality of termination conditions having a higher or lower SN value than the repeating condition presented first.

The expected reconstruction time is the time related to the CS calculation (or the total time of the time related to the CS calculation and the time related to other calculations such as image difference processing and compositing processing). The expected reconstruction time can be calculated each time based on the end condition and the image size, but in the illustrated example, the estimated reconstruction time 440 is stored in the storage device (database D) for each measurement condition. Has been done. When the candidate for the end condition is determined, the CS condition setting unit 132 reads the expected reconstruction time for each candidate from the database D and presents it to the display unit 142. The method of presentation is not particularly limited, but for example, as shown in FIG. 12, a plurality of expected reconstruction times are displayed on the display unit 142 together with the expected SN values at that time. Further, not only the SN value but also a plurality of model images having different SN values may be displayed together. As a result, the user can select an appropriate candidate in consideration of whether to prioritize the SN value or the reconstruction time.

When the user is presented on the display unit 142 and selects a predetermined expected reconstruction time from the options, the CS condition setting unit 132 accepts the selection (S425) and sets the end condition corresponding to the selected expected reconstruction time. (S426). After that, performing the CS calculation (S405 to S406) is the same as in the first embodiment.

According to the present embodiment, by presenting the expected reconstruction time, the user can more appropriately optimize the CS calculation time in consideration of the purpose of imaging and the like.

In the flow of FIG. 10, the repetition condition automatically calculated in S421 and the SN value at that time are first presented, and the candidate of the repetition condition is determined based on the result. However, S421 and S422 are omitted and the repetition is performed. Candidate conditions may be presented.
Further, as a modification of the present embodiment, instead of determining a plurality of candidates in S423, the required minimum SN value is determined, the expected reconstruction time is presented to the user, and the SN value or expected re-representation presented by the user. It may be configured to accept changes in the configuration time. Then, based on the changed SN value or the expected reconstruction time, the corresponding end condition is set.

<< CS Control Embodiment 4 >>
In the above-described first to third embodiments, the thinning rate at the time of measurement is set to a fixed value, but the present embodiment is characterized in that the thinning rate can be adjusted as a CS condition. In the present embodiment, the SN prediction formula (FIG. 5) used in the first embodiment is prepared for each thinning rate.
Hereinafter, the processing procedure of the present embodiment will be described using the flow shown in FIG. In FIG. 13, the same processing as the flow of FIG. 11 used in the third embodiment is indicated by the same reference numerals, and detailed description thereof will be omitted.

The processing from S402 to S424 of the CS condition setting unit 132 is almost the same as that of the third embodiment, but in the present embodiment, since the thinning rate is the adjustment target, before the measurement (step S401 in FIG. 10 etc.). Determine the CS conditions.
Further, in S402, the expected SN value formula 410 under each measurement condition is acquired for each of a plurality of thinning conditions (thinning ratios). Next, after acquiring the required SN value 420 at each inspection site (S403), candidates for a plurality of repetition end conditions are determined from the expected SN value formula 410 and the required SN value 420 for the inspection site (S423). The determination of the candidate in S423 is not limited, but as in the third embodiment, first, the repeating condition is determined from the desired SN, and one or more of them have a certain width. You may decide the candidate. FIG. 14 shows how candidates are determined under two different thinning conditions. In FIG. 14, the two curves LA and LB are curves showing the expected SN values when the thinning ratios are A and B (A and B are numerical values representing the thinning ratios, respectively). Here, for example, when two expected SN values higher than the required minimum SN value are used as candidates, the repetition end condition in the CS calculation is determined for each curve LA and LB, and a total of four end condition candidates are options. Next, the expected reconstruction time corresponding to each candidate is acquired from the database D450 (S424).

Next, the CS condition setting unit 132 acquires the expected measurement time under the designated measurement condition and each thinning condition from the storage unit (database E) (S431). The database E450 stores in advance the expected measurement time when measured under a plurality of thinning conditions for each measurement condition as a table or a graph (function). From this, the expected measurement time of each thinning rate is read under the specified measurement conditions. The CS condition setting unit 132 presents the expected reconstruction time acquired in S424 and the estimated measurement time acquired in S431 for each candidate. At the same time, the SN value obtained at the presented expected reconstruction time may be presented. FIG. 15 shows an example of the display. In this example, the total time of the expected measurement time and the expected reconstruction time is also displayed. As a result, the user can select an appropriate candidate in consideration of which of the SN value and the time required for measurement (measurement time, reconstruction time, or total time) is prioritized.

When the user is presented on the display unit 142 and selects a predetermined candidate from the options, the CS condition setting unit 132 accepts the selection (S432) and sets the thinning rate in the measurement and the end condition in the CS calculation (S433). After that, the measurement is performed under the condition (thinning rate) set in S433, and the CS calculation is performed under the repetition condition set in S433 (S434).
According to the present embodiment, the purpose of imaging and the inspection site are determined in consideration of the time related to imaging as a whole including not only the calculation time but also the measurement time and the SN value obtained in such a time range. Optimal conditions can be set according to the situation.

In the flow shown in FIG. 13, the expected measurement time for each thinning condition is presented for each candidate of the end condition determined from the expected SN value, but only the thinning rate may be presented without using the database E. Further, instead of setting candidates for the end condition, the end condition is repeatedly determined from the expected SN value for each thinning rate as in the first embodiment, and the determined end condition or the CS calculation time at that time (expected reconstruction time) ), The thinning rate, and the expected SN value may be presented. In this case, since a plurality of thinning rates, their respective expected reconstruction times, and SN values are presented on the display unit, the user can set appropriate conditions (thinning rates) according to the measurement purpose based on the presented conditions. Included) can be selected.

Although each embodiment of the present invention has been described above, these embodiments can be appropriately combined as long as there is no technical contradiction, and some elements can be omitted or added. ..

1 ... Subject, 2 ... Static magnetic field generator, 3 ... Diagonal magnetic field generator, 4 ... Sequencer (measurement control unit), 5 ... Transmitter, 6 ... Receiver, 7 ... Signal processing unit, 8 ... Central processing device (8 ... Central processing unit ( CPU), 9 ... gradient magnetic field coil, 10 ... gradient magnetic field power supply, 11 ... high frequency transmitter, 12 ... modulator, 13 ... high frequency amplifier, 14a ... high frequency coil (transmission coil), 14b ... high frequency coil (reception coil), 15 ... Signal amplifier, 16 ... Orthogonal phase detector, 17 ... A / D converter, 18 ... Magnetic disk, 19 ... Optical disk, 20 ... Display, 21 ... ROM, 22 ... RAM, 23 ... Trackball or mouse, 24 ... Keyboard , 25 ... Operation unit, 200 ... MRI device, 110 ... Measurement unit, 120 ... Calculation unit, 121 ... CS calculation unit, 130 ... Control unit, 131 ... Measurement control unit, 132 ... CS condition setting unit, 140 ... User interface, 141 ... Input unit, 142 ... Display unit, 150 ... Storage unit, 151 ... Database.

Claims (12)

A measurement unit that acquires measurement data from the inspection target, a calculation unit that performs CS calculation based on compressed sensing using the sparse measurement data acquired by the measurement unit, and a calculation unit that reconstructs the image of the inspection target, and the calculation unit. The storage unit includes a storage unit for storing data used for the CS calculation of the above, and the storage unit, as the data, describes the relationship between the SN predicted value of the image and the compressed sensing conditions, a predetermined part in the inspection target, and a desired SN. A table that defines the relationship with and the desired SN for each cross-sectional position in the image to be inspected are stored.
The calculation unit sets the compressed sensing conditions for each of the cross-sectional positions by using the relationship between the specified measurement conditions , the table, and the SN predicted value of the image and the compressed sensing conditions. A featured diagnostic imaging device. The diagnostic imaging apparatus according to claim 1.
The image diagnostic apparatus, wherein the compressed sensing condition includes any of the end condition of the CS calculation and the thinning condition of the measurement data. The diagnostic imaging apparatus according to claim 1.
Further provided with an input unit that accepts the input of the measurement conditions,
The calculation unit is an image diagnostic apparatus characterized in that the measurement condition received by the input unit is used as the designated measurement condition. The diagnostic imaging apparatus according to claim 1.
The calculation unit creates a plurality of candidates for the compressed sensing conditions using the designated measurement conditions, the SN predicted value of the image, and the relationship between the compressed sensing conditions, and displays them on the display device. An diagnostic imaging device characterized by this. The diagnostic imaging apparatus according to claim 4.
An input unit that accepts the selection of a predetermined candidate from the plurality of candidates is further provided.
The calculation unit is an image diagnostic apparatus characterized in that a candidate accepted by the input unit is set as a condition for compressed sensing. The diagnostic imaging apparatus according to claim 1.
The calculation unit is an image diagnostic apparatus characterized in that, under the compressed sensing conditions set, the display device displays the time required for CS calculation by the calculation unit. A measurement unit that acquires measurement data from the inspection target, a calculation unit that performs CS calculation based on compressed sensing using the sparse measurement data acquired by the measurement unit, and a calculation unit that reconstructs the image of the inspection target, and the calculation unit. The storage unit includes a storage unit for storing data used for the CS calculation, and the storage unit includes the SN predicted value of the image and the termination condition of the CS calculation as the data for each different thinning rate of the measurement data. Stores the relationship with sensing conditions ,
The calculation unit is an image diagnostic apparatus characterized in that the end condition of the CS calculation is set by using the relationship corresponding to the thinning rate when the measurement unit acquires the sparse measurement data . The diagnostic imaging apparatus according to claim 7.
The calculation unit is an image diagnostic apparatus characterized in that the measurement unit calculates the measurement time for acquiring the measurement data for each of the different thinning rates and displays the measurement time on the display device. A measuring unit that collects nuclear magnetic resonance signals from the inspection target and acquires k-space data,
A measurement control unit that controls the thinning rate of k-space data acquired by the measurement unit,
It is provided with a calculation unit that reconstructs an image by performing CS calculation based on compressed sensing using k-space data acquired at a predetermined thinning rate, and a storage unit that stores data used for CS calculation of the calculation unit. As the data, the storage unit includes a table in which the relationship between the SN predicted value of the image and the compressed sensing conditions, the relationship between a predetermined part in the inspection target and the desired SN, and the image of the inspection target are determined. Stores the desired SN for each cross-sectional position in
The calculation unit sets the compressed sensing conditions for each of the cross-sectional positions by using the designated measurement conditions , the table, and the relationship between the SN predicted value of the image and the compressed sensing conditions. A featured magnetic resonance imaging device. The magnetic resonance imaging apparatus according to claim 9.
Further provided with an input unit that accepts input of at least one of the thinning rate and the user- specified SN.
The arithmetic unit using any of the decimation rate and the user-specified SN that the input unit accepts, magnetic resonance imaging and calculating at least one of the measurement time and computing time, and wherein the to be displayed on the display device apparatus. The magnetic resonance imaging apparatus according to claim 10.
The measurement control unit controls to collect the k-space data parallel to or radially along the axis of the k-space, and the number of data sequences arranged in parallel or radially according to the thinning rate received by the input unit. A magnetic resonance imaging device characterized by thinning out. A measuring unit that collects nuclear magnetic resonance signals from the inspection target and acquires k-space data,
A measurement control unit that controls the thinning rate of k-space data acquired by the measurement unit,
A calculation unit that performs CS calculation based on compressed sensing and reconstructs an image using k-space data acquired at a predetermined thinning rate, and a storage unit that stores data used for CS calculation of the calculation unit are provided. As the data, the storage unit stores the relationship between the SN predicted value of the image and the compressed sensing condition including the end condition of the CS calculation for each different thinning rate of the measurement data.
The calculation unit is a magnetic resonance imaging apparatus characterized in that the end condition of the CS calculation is set by using the relationship corresponding to the thinning rate when the measurement unit acquires sparse measurement data.

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