Functional image generation method, multi-modal medical image system and computer equipment
By generating anatomical images, the image registration and motion correction are solved by poor consistency of anatomical images and functional images in multimodal medical imaging systems, and the quality and boundary sharpness of images are improved.
Patent Information
- Application Number
- CN202310821016.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-07-05
- Publication Date
- 2025-01-10
AI Technical Summary
When the existing multimodal medical imaging system collects or reconstructs anatomical and functional images, the treatment of subjects' respiratory movements is inconsistent, resulting in poor consistency between anatomical and functional images, which in turn affects imaging quality.
By generating a four-dimensional motion field of anatomical images, image registration and motion correction are performed, and images are used to correct multiple time points of anatomical image to improve the consistency of images, and by combining the motion-corrected image data, the image blur effect caused by motion is reduced. .
It improves the registration effect of functional images and anatomical images, makes the boundaries of functional images sharper, reduces image blur caused by respiratory movement, and improves the imaging quality of images.
Smart Images
Figure CN119295516A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of medical image processing, and in particular to a functional image generation method, a multimodal medical imaging system and a computer device. Background Art
[0002] With the development of medical image processing technology, multimodal medical imaging systems are increasingly used in medical scenarios. Multimodal medical imaging systems can simultaneously acquire anatomical images and functional images.
[0003] At present, the acquisition or reconstruction of anatomical images and functional images handles the respiratory motion of the subject differently. Especially in areas that are significantly affected by respiratory motion, such as the liver or heart, inconsistent reconstruction methods will lead to poor consistency between anatomical and functional images, ultimately resulting in poor imaging quality of the fused image obtained after registration of the anatomical and functional images. Summary of the invention
[0004] Based on this, it is necessary to provide a functional image generation method, a multimodal medical imaging system and a computer device that can improve the consistency between anatomical images and functional images in order to address the above technical problems.
[0005] In a first aspect, the present application provides a method for generating a functional image, the method comprising:
[0006] Registering the anatomical images to generate a four-dimensional motion field between the anatomical images, wherein the anatomical images are generated according to a first imaging protocol, and the four-dimensional motion field includes three-dimensional coordinate information and time information;
[0007] Acquire a first functional image, and perform motion correction on the first functional image according to the four-dimensional motion field, wherein the first functional image is reconstructed according to a second imaging protocol, and the first imaging protocol and the second imaging protocol are executed synchronously;
[0008] The plurality of the first functional images after motion correction are combined to obtain a second functional image.
[0009] In one embodiment, registering the anatomical images to generate a four-dimensional motion field includes:
[0010] Selecting a reference image from the anatomical image, and preliminarily registering the remaining images in the anatomical image with the reference image to obtain preliminary transformation parameters;
[0011] Optimizing the preliminary transformation parameters based on a registration algorithm to obtain transformation parameters;
[0012] registering the anatomical image according to the transformation parameters;
[0013] In the anatomical images after registration, the displacement vector of each pixel is calculated to obtain a four-dimensional motion field between the anatomical images.
[0014] In one embodiment, acquiring the first functional image includes:
[0015] Obtaining the start and end time of the first imaging protocol;
[0016] According to the start and end time of the first imaging protocol, the first scanning data of the first functional image is cut to obtain the second imaging protocol;
[0017] The first functional image is reconstructed according to the second imaging protocol.
[0018] In one embodiment, the first imaging protocol includes a breath-hold sequence and a breathing sequence, and cutting the scan data of the first functional image includes:
[0019] Eliminating data of a breath-holding period of the subject from the first scan data according to the start and end times of the breath-holding sequence;
[0020] The remaining first scanning data are cut according to the start and end time of the respiratory sequence to obtain the second imaging protocol.
[0021] In one embodiment, performing motion correction on the first functional image according to the four-dimensional motion field includes:
[0022] The four-dimensional motion field is reused on the first functional image, wherein a time period of the four-dimensional motion field reused on the first functional image and a time period of the first functional image are aligned with each other.
[0023] In one embodiment, merging the plurality of first functional images after motion correction to obtain a second functional image comprises:
[0024] Performing motion compensation on the plurality of first functional images after motion correction, and merging and reconstructing the first functional images after motion compensation to obtain the second functional image; or,
[0025] The plurality of the first functional images after motion correction are added to a corresponding number of PET images in DICOM format to obtain the second functional image.
[0026] In one embodiment, the first imaging protocol includes a breath-hold sequence and a breathing sequence, and the plurality of the first functional images after motion correction are combined to obtain a second functional image, including:
[0027] According to the start and end time of the breath-holding sequence, data of the breath-holding time period of the subject are eliminated from the second scan data of the first functional image after motion correction;
[0028] The second scan data is combined and reconstructed to obtain the second functional image.
[0029] In one embodiment, the anatomical image comprises an MR image or an ultrasound image, and the functional image comprises a PET image or a SPET image.
[0030] In a second aspect, the present application further provides a multimodal medical imaging system, the system comprising: a first scanning module, a second scanning module and a processing module, the first scanning module and the second scanning module are respectively connected to the processing module; wherein,
[0031] The first scanning module is used to generate anatomical image data based on a first scanning sequence scan;
[0032] The second scanning module is used to generate functional imaging data based on a second scanning sequence scan;
[0033] The first scanning module and the second scanning module scan synchronously;
[0034] The processing module is used to execute the functional image generation method described in the first aspect above.
[0035] In a third aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the functional image generation method described in the first aspect are implemented.
[0036] The above-mentioned functional image generation method, multimodal medical imaging system and computer equipment obtain a four-dimensional motion field based on the sampling of anatomical images on the time axis, and correct the synchronously acquired functional images, that is, use the anatomical images at multiple time points to correct the functional images, which not only improves the consistency of the functional images with the anatomical images in the processing of respiratory motion, but also makes the boundaries of the functional images sharper, reduces the image blurring effect caused by motion, thereby improving the registration effect of the functional images and the anatomical images. BRIEF DESCRIPTION OF THE DRAWINGS
[0037] Figure 1 is a schematic flow chart of a method for generating a functional image in an embodiment;
[0038] Figure 2 is a schematic diagram of a synchronous PET / MR imaging sequence of the liver in an embodiment;
[0039] Figure 3is a schematic diagram of a cardiac synchronized PET / MR imaging sequence in an embodiment;
[0040] Figure 4 is a diagrammatic representation of PET reconstruction of a liver in one embodiment;
[0041] Figure 5 is a schematic diagram of a process for performing PET reconstruction of the liver in one embodiment;
[0042] Figure 6 is a schematic diagram of the internal structure of a multimodal medical imaging system in an embodiment;
[0043] Figure 7 It is a schematic diagram of the internal structure of a computer device in an embodiment. DETAILED DESCRIPTION
[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0045] The functional image generation method provided in the following embodiments can be applied to various types of multimodal medical imaging systems, and the multimodal medical imaging system can synchronously acquire anatomical images and functional images. Among them, the anatomical image includes an MRI (Magnetic Resonance Imaging) image or an ultrasonic image, and the functional image includes a PET (Positron Emission Computed Tomography) image or an SPET (Single Photon Emission Tomography) image. The multimodal medical imaging system includes a PET / MR system, a PET / ultrasound system, an SPET / MR system or an SPET / ultrasound system.
[0046] Before introducing the functional image generation method, the working principle and existing problems of the PET / MR system in the related art are analyzed. For the purpose of example rather than limitation, the functional image generation method is mainly introduced by taking the PET / MR system as an example. Of course, other types of multimodal medical imaging systems are also applicable to the functional image generation method provided in this application.
[0047] The PET / MR system is a large-scale functional metabolic and molecular imaging diagnostic device that includes a positron emission tomography device and a magnetic resonance imaging device, and has both PET and MR examination functions. In the integrated PET / MR system, PET images and MR images are acquired synchronously. However, the acquisition or reconstruction of PET images and MR images handles respiratory motion differently, especially in areas such as the liver or heart that are significantly affected by respiratory motion. Inconsistent reconstruction methods will result in poor consistency between PET and MR images, ultimately leading to poor imaging quality of the PET / MR images obtained after registration of the PET and MR images.
[0048] PET reconstruction uses the amplitude or phase information of the respiratory signal to divide each respiratory cycle into different bins, which are reconstructed in sequence to obtain PET images of different phases. MR often requires subjects to hold their breath for 10 to 20 seconds to ensure that image acquisition is not disturbed by respiratory movement. When the breath is held to acquire MR images, the position of the diaphragm may deviate from the range of the diaphragm's up and down movement during normal breathing. At this time, the respiratory gating reconstruction of PET will incorrectly process the PET data collected during breath holding.
[0049] In the PET / CT system, CT and PET images are acquired successively. During the PET acquisition process, the subject is in a state of even breathing, and there is no breath-holding scenario. However, in the PET / MR system, PET reconstruction often continues the reconstruction strategy in the PET / CT system, and no special processing is done on the data during the breath-holding period during the PET acquisition process. In order to solve the mismatch problem between breath-hold PET images and respiratory-gated PET images in PET / CT, a registration algorithm is used to register the two types of images. However, the acquisition time of breath-hold PET images is short and the signal-to-noise ratio is poor, so the registration effect is difficult to guarantee.
[0050] In view of the above problems, in one embodiment, Figure 1 As shown, a functional image generation method is provided, which can be run on a PET / MR system. The process includes the following steps:
[0051] Step S101, registering the anatomical images to generate a four-dimensional motion field between the anatomical images, wherein the anatomical images are generated according to a first imaging protocol, and the four-dimensional motion field includes three-dimensional coordinate information and time information.
[0052] For PET / MR systems, anatomical images include MR images. For other types of multimodal medical imaging systems, anatomical images may also include ultrasonic images. The first imaging protocol refers to a protocol for reconstructing the first scan data to obtain the anatomical image, and the first scan data is obtained based on the MR sequence scan. The four-dimensional motion field contains information in four dimensions, namely three-dimensional coordinate information and time information. The registration of anatomical images can be a rigid registration or a non-rigid registration of images obtained at different scanning periods relative to a reference image. Rigid registration can be a translation or rotation of images obtained at different scanning periods relative to a reference image. For example, the MR images generated by several MR sequences are registered, and each MR sequence acquired synchronously with PET is used as a sampling point to generate a four-dimensional motion field. Non-rigid registration can be a method using a physical model, based on the assumption that the difference between images is caused by physical deformation, so as to construct a physical model that can fit such deformation; it can also be a method using image similarity, using the spatial transformation of the image to fit the deformation of the image. For example, the MR images generated by several MR sequences are non-rigidly registered, and each MR sequence acquired synchronously with PET is used as a sampling point to generate a four-dimensional motion field.
[0053] Step S102, acquiring a first functional image, and performing motion correction on the first functional image according to the four-dimensional motion field, wherein the first functional image is reconstructed according to a second imaging protocol, and the first imaging protocol and the second imaging protocol are executed synchronously.
[0054] For PET / MR systems, functional images include PET images. For other types of multimodal medical imaging systems, anatomical images may also include SPET images. The second imaging protocol refers to a protocol for reconstructing the second scan data to obtain a functional image, and the second scan data is obtained based on a PET sequence scan. The first imaging protocol and the second imaging protocol are executed synchronously, which means that the start and end time of the first imaging protocol and the second imaging protocol are the same. Motion correction refers to reusing the four-dimensional motion field for the first functional image, wherein the time period of the four-dimensional motion field reused for the first functional image and the time period of the first functional image are aligned with each other. Exemplarily, the PET data corresponding to the MR sequence in different time periods are reconstructed separately to obtain a PET image that completely corresponds to the MR image, and the four-dimensional motion field extracted based on the MR image is reused in the PET image, so that the PET images at different time points are accurately matched in space.
[0055] Step S103 , combining the plurality of first functional images after motion correction to obtain a second functional image.
[0056] The PET data can be merged and reconstructed by using a motion compensation iterative reconstruction algorithm (Motion compensation OSEM List-mode Algorithm for Resolution recovery Reconstruction, MOLAR), or multiple PET images in DICOM format can be directly accumulated to obtain a static PET image with a high signal-to-noise ratio. For example, multiple PET images after motion correction are merged into one PET image.
[0057] In the above steps S101 to S103, taking the PET / MR system as an example, a four-dimensional motion field is obtained based on the sampling of the MR image on the time axis, and the synchronously acquired PET image is corrected, that is, the MR image at multiple time points is used to correct the PET image, which not only improves the consistency of the PET image with the MR image in the processing of respiratory motion, but also makes the PET image boundary sharper, reduces the image blurring effect caused by motion, and thus improves the registration effect of the PET image and the MR image. Moreover, this embodiment can accurately reconstruct the PET image synchronously acquired with any MR sequence, and is suitable for the scene of clinical extensive scanning of different MR sequences.
[0058] In one embodiment, registering the anatomical images to generate a four-dimensional motion field can be achieved by:
[0059] A reference image is selected from the anatomical images, and the remaining images in the anatomical images are preliminarily registered with the reference image to obtain preliminary transformation parameters; the preliminary transformation parameters are optimized based on the registration algorithm to obtain transformation parameters; the anatomical images are registered according to the transformation parameters; in the anatomical images after completion of the registration, the displacement vector of each pixel is calculated to obtain the four-dimensional motion field between the anatomical images.
[0060] Taking non-rigid registration as an example, first, the MR data is preprocessed, such as smoothing, denoising, correcting image deflection or estimating motion artifacts, to improve image quality and registration results. For each MR image, a corresponding feature extraction algorithm is used to extract key structural features, such as brain regions, blood vessels or anatomical structures, to ensure that the extracted features have good correspondence in all images. After the feature extraction is completed, a reference image is selected as a fixed image, and all other images are preliminarily registered to obtain preliminary transformation parameters. Next, a non-rigid registration algorithm (such as a physical model-based method or an image similarity-based method) is used to further optimize the preliminary transformation parameters so that it can better fit the correspondence of feature points. This can involve using a deformation field or displacement field model to optimize the registration objective function to obtain the best non-rigid transformation. After completing the non-rigid registration, an interpolation method can be used to estimate the motion field between images, which can be done by calculating the displacement vector of each pixel. The motion field can be represented as a four-dimensional motion field in three-dimensional space, where the fourth dimension represents time.
[0061] In one embodiment, obtaining the first functional image may be achieved by:
[0062] The start and end times of the first imaging protocol are obtained; according to the start and end times of the first imaging protocol, the first scan data of the first functional image is cut to obtain the second imaging protocol; according to the second imaging protocol, the first functional image is reconstructed. Wherein, the first imaging protocol includes a breath-hold sequence and a breathing sequence. When cutting the scan data of the first functional image, the data of the breath-hold time period of the subject can be eliminated from the first scan data according to the start and end times of the breath-hold sequence; according to the start and end times of the breathing sequence, the remaining first scan data is cut to obtain the second imaging protocol.
[0063] For example, Figure 2 A schematic diagram of the liver synchronous PET / MR imaging sequence is given. Figure 3 A schematic diagram of the cardiac synchronized PET / MR imaging sequence is given. Figure 2 During the 15-minute PET acquisition period, MR synchronously acquired 11 sequences, including 4 respiratory gating sequences (2min, 3min, 3min, 3min) and 7 breath-hold sequences (16s, 16s, 16s, 16s, 16s, 16s, 16s). The 11 sequences correspond to 11 sampling points, and each sampling point corresponds to a four-dimensional motion field. Figure 3During the 15-minute PET acquisition period, MR synchronously acquired 13 sequences, including 1 respiratory gating sequence (2min) and 12 breath-holding sequences (16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s, 16s). The 13 sequences correspond to 13 sampling points, respectively, and each sampling point corresponds to a four-dimensional motion field. During respiratory gating acquisition, the subject is in a free-breathing state. During breath-hold acquisition, the subject is in a state of holding the breath at the end of inspiration or expiration. At this time, the diaphragm position has deviated from the range of motion of the diaphragm during normal breathing. This embodiment does not require additional generation of MR sequences to extract the four-dimensional motion field, and can cover the entire PET acquisition process, reduce patient scanning time, reduce equipment occupancy time, can distinguish between breath-holding / breathing states, and support the acquisition of patient displacement information over a longer period of time.
[0064] In one embodiment, merging the plurality of first functional images after motion correction to obtain the second functional image can be achieved by the following methods:
[0065] Method 1: Motion compensation is performed on multiple first functional images after motion correction, and the first functional images after motion compensation are merged and reconstructed to obtain a second functional image. In this way, a static PET image with a high signal-to-noise ratio is obtained.
[0066] Method 2: The plurality of first functional images after motion correction are accumulated with a corresponding number of PET images in DICOM format to obtain a second functional image. In this way, a static PET image with a high signal-to-noise ratio is obtained.
[0067] Method three: The first imaging protocol includes a breath-hold sequence and a breathing sequence. According to the start and end time of the breath-hold sequence, the data of the subject's breath-holding period is eliminated from the second scan data of the first functional image after motion correction; the second scan data is merged and reconstructed to obtain a second functional image.
[0068] Exemplarily, the PET data of the time period corresponding to the MR breath-hold sequence is eliminated. This is because the total time of the MR breath-hold sequence is relatively short, and eliminating these data has little effect on the signal-to-noise ratio of the PET image. This setting can reduce the calculation time when the signal-to-noise ratio of the PET image is reduced to a tolerable level. The remaining PET data are merged and reconstructed into a PET image, that is, the MR respiratory gating sequences collected separately at different time points are not aligned. This is because the probability of body displacement during MR examination is small. The specific operations are as follows: identify the start time and end time of the breath-hold MR sequence; find the PET data corresponding to these breath-hold sequences, and eliminate the PET data in these time periods; merge and reconstruct the remaining PET data into a PET image.
[0069] Combination Figure 2 Liver PET / MR imaging, Figure 4 A diagrammatic schematic diagram of PET reconstruction of the liver is given. Among them, MR-1 represents the first MR image and is used as a reference image for registration in this embodiment, t1 represents the first scanning period; MR-2 represents the second MR image and is used as a floating-point image in this embodiment, t2 represents the second scanning period, and registration R(2-1) represents the transformation matrix between MR-2 and MR-1; and so on, MR-N represents the Nth (N can be 3, 4, ···) MR image and is used as a floating-point image in this embodiment, tN represents the Nth scanning period, and registration R(N-1) represents the transformation matrix between MR-N and MR-1.
[0070] The essence of the 4D motion field is the transformation matrix of XYZ plus time; PET-01 represents the original PET image; PET-1 represents the PET image corresponding to MR-1 split out from the first scanning period; PET-02 represents the new PET image synthesized after motion correction in the second scanning period; and so on, PET-N represents the Nth (N can be 3, 4,...) motion-corrected image. Figure 4 , Figure 5 A schematic diagram of the process of PET reconstruction of the liver is given, which includes the following steps:
[0071] Step S201, non-rigid registration is performed on the images generated by 11 MR sequences to generate a four-dimensional motion field. First, the MR data is preprocessed, such as smoothing, denoising, correcting image deflection or estimating motion artifacts, to improve image quality and registration results. For each MR image, a specific feature extraction algorithm is used to extract key structural features, such as brain regions, blood vessels or anatomical structures, to ensure that the extracted features have a good correspondence in all images. After the feature extraction is completed, a reference image is selected as a fixed image, and all other images are preliminarily registered to obtain preliminary transformation parameters. Next, a non-rigid registration algorithm (such as a method based on a physical model or a method based on image similarity) is used to further optimize the preliminary transformation parameters so that it can better fit the correspondence between feature points, which may involve the use of a deformation field or a displacement field model to obtain the best non-rigid transformation by optimizing the registration objective function. After completing the non-rigid registration, an interpolation method can be used to estimate the motion field between images. This can be done by calculating the displacement vector of each pixel. The motion field can be represented as a four-dimensional motion field in three-dimensional space, where the fourth dimension represents time.
[0072] Step S202, reconstruct the PET data corresponding to the MR sequences in different time periods. Reconstruct the PET data corresponding to the MR sequences in different time periods. Read the start and end time of each MR sequence scan, and pass the time to the PET subsystem. Cut the PET data according to the start and end time of the transmitted MR sequence, so as to obtain a section of PET raw data that completely corresponds to the MR. Reconstruct the obtained PET raw data to obtain a PET image that completely corresponds to the transmitted MR image. Transmit the information of multiple MR sequences in sequence and reconstruct multiple PET data that completely correspond to the MR in sequence.
[0073] Step S203, motion correction is performed on the PET image using the four-dimensional motion field generated based on the MR sequence. The PET image is motion corrected using the four-dimensional motion field generated based on the MR sequence. Step S201 obtains the four-dimensional motion field through non-rigid registration of multiple MR sequences, and step S202 obtains a PET image that completely corresponds to MR. Therefore, the motion field extracted from MR can be reused in the PET image obtained in step S202, so that the PET images at different time points can be accurately matched in space. The key point is to reuse the motion field extracted from the structural image such as MR into the functional image with unclear boundaries, so that the image boundary of the functional image is sharper and the matching with the synchronously collected structural image is more accurate.
[0074] Step S204, merging the 11 motion-corrected PET images into one PET image. Merging the 11 motion-corrected PET images into one PET image. Merging and reconstructing the PET data using a motion compensation iterative reconstruction algorithm (Motion compensation OSEM List-mode Algorithm for Resolution recovery Reconstruction, MOLAR) or directly adding up the 11 DICOM format PET images can both yield a static PET image with a high signal-to-noise ratio.
[0075] Optionally, in the above step 204, the following method may be used instead:
[0076] Eliminate the PET data of the time period corresponding to the MR breath-hold sequence. This is because the total time of the MR breath-hold sequence is relatively short, and eliminating this data has little effect on the signal-to-noise ratio of the PET image. This setting can reduce the calculation time when the signal-to-noise ratio of the PET image is reduced to a tolerable level. Merge the remaining PET data and reconstruct it into a PET image, that is, the MR respiratory gating sequences collected at different time points are not aligned. This is because the probability of body displacement during MR examination is small. The specific operations are as follows: identify the start time and end time of the breath-hold MR sequence; find the PET data corresponding to these breath-hold sequences, and eliminate the PET data in these time periods; merge and reconstruct the remaining PET data into a PET image.
[0077] In one embodiment, Figure 6 As shown, a multimodal medical imaging system is provided, the system includes: a first scanning module, a second scanning module and a processing module, the first scanning module and the second scanning module are respectively connected to the processing module; wherein the first scanning module is used to generate anatomical image data based on a first scanning sequence scanning; the second scanning module is used to generate functional image data based on a second scanning sequence scanning; the first scanning module and the second scanning module scan synchronously; the processing module is used to execute the functional image generation method of any of the above embodiments. The implementation scheme for solving the problem provided by the multimodal medical imaging system is similar to the implementation scheme recorded in the above method, so the specific limitations in this embodiment or the following multimodal medical imaging system embodiments can refer to the limitations on the functional image generation method in the above text, and will not be repeated here.
[0078] Multimodal medical imaging systems can simultaneously acquire anatomical images and functional images. The anatomical images include MR (Magnetic Resonance Imaging) images or ultrasound images, and the functional images include PET (Positron Emission Computed Tomography) images or SPET (Single Photon Emission Tomography) images. Multimodal medical imaging systems include PET / MR systems, PET / ultrasound systems, SPET / MR systems, or SPET / ultrasound systems.
[0079] Each module in the above multimodal medical imaging system can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.
[0080] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a functional image generation method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.
[0081] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0082] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: aligning anatomical images to generate a four-dimensional motion field between the anatomical images, wherein the anatomical images are generated according to a first imaging protocol, and the four-dimensional motion field includes three-dimensional coordinate information and time information; acquiring a first functional image, and performing motion correction on the first functional image according to the four-dimensional motion field, wherein the first functional image is reconstructed according to a second imaging protocol, and the first imaging protocol and the second imaging protocol are executed synchronously; and merging multiple first functional images after motion correction to obtain a second functional image.
[0083] In one embodiment, the processor also implements the following steps when executing the computer program: selecting a reference image in the anatomical image, preliminarily registering the remaining images in the anatomical image with the reference image to obtain preliminary transformation parameters; optimizing the preliminary transformation parameters based on the registration algorithm to obtain transformation parameters; registering the anatomical images according to the transformation parameters; and calculating the displacement vector of each pixel in the anatomical image after the registration to obtain a four-dimensional motion field between the anatomical images.
[0084] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the start and end time of the first imaging protocol; cutting the first scanning data of the first functional image according to the start and end time of the first imaging protocol to obtain the second imaging protocol; and reconstructing the first functional image according to the second imaging protocol.
[0085] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the start and end times of the breath-hold sequence, data of the subject's breath-hold time period are eliminated from the first scan data; according to the start and end times of the breathing sequence, the remaining first scan data are cut to obtain a second imaging protocol.
[0086] In one embodiment, when the processor executes the computer program, the following steps are further implemented: multiplexing the four-dimensional motion field for the first functional image, wherein the time period of the four-dimensional motion field multiplexed for the first functional image and the time period of the first functional image are aligned with each other.
[0087] In one embodiment, when the processor executes the computer program, the following steps are further implemented: performing motion compensation on the plurality of first functional images after motion correction, and merging and reconstructing the first functional images after motion compensation to obtain a second functional image; or
[0088] The plurality of first functional images after motion correction are accumulated with a corresponding number of PET images in DICOM format to obtain a second functional image.
[0089] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the start and end time of the breath-holding sequence, in the second scan data of the first functional image after motion correction, the data of the breath-holding time period of the subject is eliminated; and the second scan data is merged and reconstructed to obtain a second functional image.
[0090] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: aligning anatomical images to generate a four-dimensional motion field between the anatomical images, wherein the anatomical images are generated according to a first imaging protocol, and the four-dimensional motion field includes three-dimensional coordinate information and time information; acquiring a first functional image, and performing motion correction on the first functional image according to the four-dimensional motion field, wherein the first functional image is reconstructed according to a second imaging protocol, and the first imaging protocol and the second imaging protocol are executed synchronously; and merging multiple first functional images after motion correction to obtain a second functional image.
[0091] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: selecting a reference image in the anatomical image, preliminarily registering the remaining images in the anatomical image with the reference image, and obtaining preliminary transformation parameters; optimizing the preliminary transformation parameters based on the registration algorithm to obtain transformation parameters; registering the anatomical images according to the transformation parameters; and calculating the displacement vector of each pixel in the anatomical image after the registration to obtain a four-dimensional motion field between the anatomical images.
[0092] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: obtaining the start and end time of the first imaging protocol; cutting the first scanning data of the first functional image according to the start and end time of the first imaging protocol to obtain a second imaging protocol; and reconstructing the first functional image according to the second imaging protocol.
[0093] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: according to the start and end times of the breath-hold sequence, data of the subject's breath-hold period are eliminated from the first scan data; according to the start and end times of the breathing sequence, the remaining first scan data are cut to obtain a second imaging protocol.
[0094] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: multiplexing the four-dimensional motion field for the first functional image, wherein the time period of the four-dimensional motion field multiplexed for the first functional image and the time period of the first functional image are aligned with each other.
[0095] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: performing motion compensation on multiple first functional images after motion correction, and merging and reconstructing the motion compensated first functional images to obtain a second functional image; or, accumulating a corresponding number of PET images in DICOM format on the multiple first functional images after motion correction to obtain a second functional image.
[0096] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the start and end times of the breath-holding sequence, in the second scan data of the motion-corrected first functional image, data of the subject's breath-holding period are eliminated; and the second scan data are merged and reconstructed to obtain a second functional image.
[0097] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.
[0098] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.
[0099] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0100] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A method for generating a functional image, characterized in that: The method comprises: Registering the anatomical images to generate a four-dimensional motion field between the anatomical images, wherein the anatomical images are generated according to a first imaging protocol, and the four-dimensional motion field includes three-dimensional coordinate information and time information; Acquire a first functional image, and perform motion correction on the first functional image according to the four-dimensional motion field, wherein the first functional image is reconstructed according to a second imaging protocol, and the first imaging protocol and the second imaging protocol are executed synchronously; The plurality of the first functional images after motion correction are combined to obtain a second functional image.
2. The method for generating functional images according to claim 1, characterized in that: The anatomical images are registered to generate a 4D motion field, including: Selecting a reference image from the anatomical image, and preliminarily registering the remaining images in the anatomical image with the reference image to obtain preliminary transformation parameters; Optimizing the preliminary transformation parameters based on a registration algorithm to obtain transformation parameters; registering the anatomical image according to the transformation parameters; In the anatomical images after registration, the displacement vector of each pixel is calculated to obtain a four-dimensional motion field between the anatomical images.
3. The method for generating functional images according to claim 1, characterized in that: Obtain the first functional image, including: Obtaining the start and end time of the first imaging protocol; According to the start and end time of the first imaging protocol, the first scanning data of the first functional image is cut to obtain the second imaging protocol; The first functional image is reconstructed according to the second imaging protocol.
4. The method for generating functional images according to claim 3, characterized in that: The first imaging protocol includes a breath-hold sequence and a breathing sequence, and cutting the scan data of the first functional image includes: Eliminating data of a breath-holding period of the subject from the first scan data according to the start and end time of the breath-holding sequence; The remaining first scanning data are cut according to the start and end time of the respiratory sequence to obtain the second imaging protocol.
5. The method for generating functional images according to claim 1, characterized in that: Performing motion correction on the first functional image according to the four-dimensional motion field includes: The four-dimensional motion field is reused on the first functional image, wherein a time period of the four-dimensional motion field reused on the first functional image and a time period of the first functional image are aligned with each other.
6. The method for generating functional images according to claim 1, characterized in that: Combining the plurality of the first functional images after motion correction to obtain a second functional image includes: Performing motion compensation on the plurality of first functional images after motion correction, and merging and reconstructing the first functional images after motion compensation to obtain the second functional image; or, The plurality of the first functional images after motion correction are added to a corresponding number of PET images in DICOM format to obtain the second functional image.
7. The method for generating functional images according to claim 1, characterized in that: The first imaging protocol includes a breath-hold sequence and a breathing sequence, and the plurality of the first functional images after motion correction are combined to obtain a second functional image, including: According to the start and end time of the breath-holding sequence, data of the breath-holding time period of the subject are eliminated from the second scan data of the first functional image after motion correction; The second scan data is combined and reconstructed to obtain the second functional image.
8. The method for generating functional images according to claim 1, characterized in that: The anatomical images include MR images or ultrasonic images, and the functional images include PET images or SPET images.
9. A multimodal medical imaging system, characterized in that: The system comprises: a first scanning module, a second scanning module and a processing module, wherein the first scanning module and the second scanning module are respectively connected to the processing module; wherein, The first scanning module is used to generate anatomical image data based on a first scanning sequence scan; The second scanning module is used to generate functional imaging data based on a second scanning sequence scan; The first scanning module and the second scanning module scan synchronously; The processing module is used to execute the functional image generation method according to any one of claims 1 to 8.
10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the functional image generation method according to any one of claims 1 to 8 are implemented.