KR20210110236A - System and method for registrating multiple images - Google Patents

Abstract

Disclosed are a system for PET-MRI multi image matching and a method. According to an embodiment of the technology, it is possible to minimize noise and error caused by movements of an object during photographing as each sinogram data is acquired from raw data obtained through PET and MRI respectively and is matched in each acquired sinogram area, and to improve quality of a restored image.

Description

PET-MRI multi-image registration system and method

The present invention relates to a PET-MRI multiple image registration system and method, and more particularly, each sinogram area obtained after acquiring each sinogram data from raw data acquired through PET and MRI, respectively. By mutual registration in , it is possible to minimize noise and errors due to the movement of an object during photographing, and thus relates to a technology to improve image quality.

Medical images used for cellular, preclinical, clinical trials, and patient diagnosis are generally classified into structural images and functional images. The structural image refers to an image of the structure and anatomy of the human body, and the functional image is to image functional information on cognition and sensory function of the human body in a direct or indirect way.

Structural and anatomical imaging technologies include Computed Tomography (CT), Magnetic Resonance Imaging (MRI), etc., and a technology to image functional information by observing physiological and biochemical actions of the human body. Positron emission tomography (PET) is widely used as a method.

In order to use both MRI and PET images obtained from a sequential PET-MRI imaging apparatus or individual imaging apparatuses, mutual registration between multiple images is essential because of differences in the position and posture of an object during each image capture. In addition, even in the case of an integrated PET-MRI imaging apparatus, if the images are not obtained at the same time, mutual registration may be required due to the movement of the object between imaging.

Existing multi-image mutual registration methods are image-based mutual registration methods that perform registration by adjusting the position and posture of an object in two images in an image domain after reconstructing an image. Multiple images are often used to improve reconstruction of individual images or to correct physical phenomena within images. can proceed. Due to this, there is a burden that redundant image reconstruction occurs.

Therefore, the technical problem to be achieved by the present invention is to obtain each sinogram data from raw data obtained through PET and MRI, and then mutually match each of the obtained sinogram regions. An object of the present invention is to provide a PET-MRI multi-image registration system and method capable of minimizing noise and errors due to motion and improving image quality.

The object of the present invention is not limited to the object mentioned above, and other objects and advantages of the present invention not mentioned can be understood by the following description, and will be more clearly understood by the examples of the present invention. It will also be readily apparent that the objects and advantages of the present invention can be realized by means of the means and combinations thereof indicated in the claims.

According to these features, the PET-MRI multiple image registration system according to an embodiment is

a raw data acquisition unit configured to acquire raw data from each of positron emission computed tomography (PET) and magnetic resonance imaging (MRI); a preprocessor for obtaining sinogram data for each of the raw data obtained from the PET and MRI; It is characterized in that it includes a matching unit that compares the acquired sinogram data, matches each sinogram area so that the position and posture of each object match, and transmits the matching to the reconstructing unit.

Preferably, the preprocessor may include a PET sinogram acquisition module for acquiring sinogram data from raw data of the PET image in the case of radiation detection information, and when the raw data of the acquired PET image is radiation detection order information, the PET image is acquired. It may further include a PET conversion module that converts the signomo image and then transmits it to the PET signogram acquisition module.

Preferably, the preprocessor may include an MRI sinogram acquisition module that acquires sinogram data by performing inverse one-dimensional Fourier transform when raw data of frequency components constituting k-space obtained from MRI is a radiation coordinate system. When the raw data of the frequency component constituting the k-space obtained from the rectangular coordinate system is a rectangular coordinate system, the method may further include an MRI transformation module that converts the raw data into a radiation coordinate system and then transmits the raw data to the MRI sinogram acquisition module.

A PET-MRI multi-image registration method according to an embodiment includes: a raw data acquisition step of acquiring raw data from each of positron emission computed tomography (PET) and magnetic resonance imaging (MRI); a preprocessing step of obtaining sinogram data for each of the raw data obtained from the PET and MRI; and a matching step of comparing the acquired sinogram data, matching each sinogram area so that the position and posture of each object match, and transferring the matched to the reconstructing unit.

Preferably, the pre-processing step may include a PET sinogram acquisition step of acquiring sinogram data from raw PET data in the case of radiation detection information. The method may further include a PET conversion step of converting into a signomo image and then transferring the converted to the PET signogram obtaining step.

Preferably, the pre-processing step may include an MRI sinogram acquisition step of obtaining sinogram data by performing inverse one-dimensional Fourier transform when raw data of frequency components constituting k-space obtained from MRI is a radial coordinate system, When the raw data of the frequency components constituting the k-space obtained from the MRI is a rectangular coordinate system, the method may further include an MRI transformation step of converting the raw data into a radiation coordinate system and then transferring the raw data to the MRI sinogram acquisition step.

According to an embodiment, as each sinogram data is acquired from raw data acquired through PET and MRI, and then mutually matched in each acquired sinogram region, noise caused by the movement of the object during imaging and errors can be minimized, and thus the restored image quality can be improved.

The following drawings attached to this specification illustrate preferred embodiments of the present invention, and serve to further understand the technical spirit of the present invention together with the detailed description of the present invention to be described later, so the present invention is a matter described in such drawings should not be construed as being limited only to
1 is a block diagram of a PET-MRI multi-image registration system according to an embodiment.
2 and 3 are detailed configuration diagrams of a preprocessor of a system according to an exemplary embodiment.
4 is an overall flowchart of a PET-MRI multi-image registration process according to another embodiment.

Specific structural or functional descriptions of the embodiments are disclosed for purposes of illustration only, and may be changed and implemented in various forms. Accordingly, the embodiments are not limited to a specific disclosure form, and the scope of the present specification includes changes, equivalents, or substitutes included in the technical spirit.

Although terms such as first or second may be used to describe various components, these terms should be interpreted only for the purpose of distinguishing one component from another. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

When a component is referred to as being “connected to” another component, it may be directly connected or connected to the other component, but it should be understood that another component may exist in between.

The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that the described feature, number, step, operation, component, part, or combination thereof exists, and includes one or more other features or numbers, It should be understood that the possibility of the presence or addition of steps, operations, components, parts or combinations thereof is not precluded in advance.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present specification. does not

Hereinafter, the present invention will be described in detail by describing preferred embodiments of the present invention with reference to the accompanying drawings.

FIG. 1 is a diagram showing the configuration of a PET-MRI multiple image registration system according to an embodiment, FIG. 2 is a detailed configuration diagram of a preprocessor for raw PET data shown in FIG. 1, and FIG. 3 is a diagram shown in FIG. It is a detailed configuration diagram of the low processing unit for the raw data of MRI.

1 to 3 , a PET-MRI multi-image registration system according to an embodiment acquires each sinogram data from raw data acquired through PET and MRI, respectively, and then acquires each sinogram. It is configured to reconstruct after mutual matching in the gram region, and thus the system may include a raw data acquisition unit 100 , a preprocessor 200 , and a matching unit 300 .

Here, the raw data acquisition unit 100 may acquire raw data from each of positron emission computed tomography (PET) and magnetic resonance imaging (MRI). That is, the raw data acquisition unit 100 may derive digital raw data having a scanning loop of a predetermined sampling rate from the PET analog signal and transmit it to the preprocessing unit 200 . Although a series of processes for deriving raw data in digital form from a PET analog signal is not specifically specified in this specification, it should be understood at the level of those skilled in the art. In this case, the raw data may be one of radiation detection information or radiation detection order information.

Meanwhile, the raw data acquisition unit 100 may derive raw data of frequency components constituting the k-space acquired from MRI that non-invasively acquires anatomical and functional image information inside human tissue. Then, the derived raw data of the k-space is transmitted to the preprocessor 200 . Here, raw data in k-space is represented by either a radiation coordinate system or a rectangular coordinate system. In the present specification, a series of processes for outputting raw data of k-space obtained from MRI is not specifically specified, but it should be understood at the level of those skilled in the art.

Accordingly, the preprocessor 200 may receive raw data of PET and raw data of MRI, obtain respective sinogram data, and then transmit each of the acquired sinogram data to the matching unit 200 . Accordingly, as shown in FIGS. 2 and 3 , the preprocessor 200 includes a PET sinogram acquisition module 210 , a PET transformation module 220 , an MRI sinogram acquisition module 230 , and an MRI transformation module 240 . may include at least one of

Here, when the obtained raw data is radiation detection information, the PET sinogram acquisition module 210 classifies the data according to the period in which the object moves and generates the sinogram data from the classified raw data. That is, first to Nth groups are gated according to a period in which the object moves, and first to Nth sinograms for the first to Nth groups are generated. Accordingly, the first to Nth sinograms are not included in the call according to the movement. For example, when a first sinogram for any one state among a plurality of states according to the breathing movement of the object is generated, the states of the object are similarly repeated in each breathing cycle within one breathing cycle. If the breathing cycle of the object is about 1 cycle/5 sec, the state of the object is similar at 1 second, 6 second, 11 second, etc., and becomes similar at 2 second, 7 second, 12 second, etc. 210) generates a first sinogram based on the data obtained when the detection time is 1 second, 6 seconds, 11 seconds, etc., and makes a second based on the data obtained when the detection time is 2 seconds, 7 seconds, 12 seconds 2 Create a sinogram. Similarly, third to Nth sinograms are generated.

On the other hand, when the obtained raw data is radiation detection order information, the obtained raw data is transmitted to the PET conversion module 220 , and the PET conversion module 220 converts the obtained PET image into a sinogram image and then the converted sig The nomo image is transmitted to the PET sinogram obtaining module 210 , and the PET sinogram obtaining module 210 may derive sinogram data from the converted signomorphic image.

In addition, when raw data obtained from MRI is a radiation coordinate system, raw data in k-space is transmitted to the MRI sinogram obtaining module 230, and the MRI sinogram obtaining module 230 is a frequency constituting k-space obtained from the MRI. Inverse one-dimensional Fourier transform is performed on the raw data of the component, and then the sinogram data is obtained.

And, when the raw data obtained from the MRI is a rectangular coordinate system, the raw data in k-space is transmitted to the MRI conversion module 240 , and the MRI conversion module 240 obtains raw data of frequency components constituting the k-space obtained from the MRI. is converted into a radiation coordinate system and then transferred to the MRI sinogram acquisition module 230 .

Each of the sinogram data of the PET sinogram acquisition module 210 and the MRI sinogram acquisition module 230 is transmitted to the matching unit 300, and the matching unit 300 receives the sinograms obtained for each sinogram area. By comparing the data, registration is performed in which the position and posture of each object are matched.

That is, the matching unit 300 can estimate the motion of the sinogram through comparison of each sinogram data for each sinogram area, and can estimate the motion through the movement information of the center value for each angle in this sinogram, The motion of the sinogram can be corrected by applying it inversely through the estimated motion.

Accordingly, according to an exemplary embodiment, noise and errors due to the movement of an object during photographing may be minimized, and thus the restored image quality may be improved.

4 is a flowchart illustrating a PET-MRI multi-image registration process according to an exemplary embodiment. A PET-MRI multi-image registration method according to another exemplary embodiment will be described with reference to FIG. 3 .

According to an embodiment, in steps S10, S11, and S12, the pre-processing unit 200 according to an embodiment of the present invention is performed when the raw data acquired from PET in the raw data acquisition unit 100 of FIG. 1 is radiographic information. Acquire sinogram data.

If the raw data obtained from PET in step S11 is not radiographic information, in step S13, the preprocessor 200 of an embodiment determines the radiation detection sequence information to convert the PET image into a sinogram image, and then The process proceeds to step S12.

Meanwhile, in step S21, when the raw data on k-space obtained from the MRI is a radial coordinate system, the preprocessor 200 proceeds to step S22, and in step S22, the preprocessor 200 performs the MRI Sinogram data is obtained by performing inverse one-dimensional Fourier transform on raw data of frequency components constituting k-space obtained from .

However, if the raw data in k-space obtained from the MRI in step S21 is not a radial coordinate system, it is determined as a rectangular coordinate system and proceeds to step S23, and in step S23, the preprocessor 200 of an embodiment is The data is converted into a radiation coordinate system and then proceeds to step S22.

Then, in step S30 , each sinogram data is transmitted to the matching unit 300 , and the matching unit 300 compares the acquired sinogram data for each sinogram area to match the position and posture of each object. perform matching.

Accordingly, it is possible to minimize noise and errors due to the movement of the object during photographing, and thus the restored image quality can be improved.

The embodiments described above may be implemented by a hardware component, a software component, and/or a combination of a hardware component and a software component. For example, the apparatus, methods and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate (FPGA) array), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, may be implemented using one or more general purpose or special purpose computers. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

Software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or device, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems, and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the computer-readable medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floppy disks. Included are magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order than the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

100: raw data acquisition unit
200: preprocessor
210: PET sinogram acquisition module
220: PET conversion module
230: MRI sinogram acquisition module
240: MRI conversion module
300: matching part

Claims (10)

a raw data acquisition unit configured to acquire raw data from each of positron emission computed tomography (PET) and magnetic resonance imaging (MRI);
a preprocessor for obtaining sinogram data for each of the raw data obtained from the PET and MRI;
Comparing the acquired sinogram data, the PET-MRI multiple image registration system comprising a matching unit that matches each sinogram area so that the position and posture of each object match, and transmits the matching to the reconstruction unit. According to claim 1, wherein the pre-processing unit,
PET-MRI multiple image registration system, comprising a PET sinogram acquisition module for acquiring sinogram data in case of radiation detection information from raw data of PET images. The method of claim 2, wherein the pre-processing unit
When the raw data of the acquired PET image is radiation detection sequence information, the PET-MRI multi-image further comprising a PET conversion module that converts the PET image into a signomo image and then transmits it to the PET signogram acquisition module. matching system. The method of claim 2, wherein the pre-processing unit
PET-MRI multi-image registration comprising an MRI sinogram acquisition module that acquires sinogram data by performing one-dimensional Fourier inverse transform when raw data of frequency components constituting k-space acquired from MRI is a radiation coordinate system. system. The method of claim 4, wherein the pre-processing unit,
When the raw data of the frequency components constituting the k-space obtained from the MRI is a rectangular coordinate system, the MRI conversion module further comprises an MRI conversion module that converts the raw data into a radiation coordinate system and then transmits it to the MRI sinogram acquisition module. MRI multi-image registration system. a raw data acquisition step of acquiring each raw data from each of positron emission computed tomography (PET) and magnetic resonance imaging (MRI);
a preprocessing step of obtaining sinogram data for each of the raw data obtained from the PET and MRI;
A PET-MRI multiple image registration method, comprising: a matching step of comparing the acquired sinogram data, matching each sinogram area so that the position and posture of each object match, and transmitting the matching to the reconstruction unit. The method of claim 6, wherein the pretreatment step,
PET-MRI multiple image registration method comprising the step of acquiring a PET sinogram of acquiring sinogram data in the case of radiation detection information from raw data of a PET image. The method of claim 7, wherein the pretreatment step
PET-MRI multi-image registration, characterized in that when the raw data of the obtained PET image is radiation detection order information, the PET image is converted into a signomo image, and then the PET conversion step of obtaining the PET sinogram is further included. Way. The method of claim 6, wherein the pre-treatment step,
PET-MRI multi-image registration comprising: obtaining sinogram data by performing one-dimensional Fourier inverse transform when raw data of frequency components constituting k-space obtained from MRI is a radiation coordinate system; Way. 10. The method of claim 9, wherein the pre-processing unit,
When raw data of frequency components constituting k-space obtained from MRI is a rectangular coordinate system, converting the raw data into a radiation coordinate system and then performing the MRI sinogram acquisition step PET- MRI multi-image registration method.

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