Bimodal registration device and automatic registration method for small animal MPI-CT combined imaging

Abstract

The present invention belongs to the field of biomedical imaging, and specifically relates to a bimodal registration device for small animal MPI-CT joint imaging and an automatic registration method thereof, aiming to solve the problem that the registration markers of the existing small animal MPI-CT joint imaging are placed according to the experience of the experimenter, and it is difficult to achieve complete three-dimensional registration. The present invention includes: the marker material includes an MPI tracer for MPI imaging and a CT contrast agent for CT imaging; the bimodal registration marker includes a glass capillary and a flexible PVC tube, the glass capillary is filled with an MPI tracer, the outer layer of the glass capillary is surrounded by a layer of flexible PVC tube, and the CT contrast agent is filled between the outer wall of the glass capillary and the inner wall of the flexible PVC tube; the support frame is used to fix three bimodal registration markers, and the support frame is arranged directly above the imaging part. The present invention uses a bimodal registration device to achieve high-precision three-dimensional automatic registration of MPI images and CT images through an automatic registration method without replacing the marker when alternating imaging modes.

Description

Background Art

[0002] Magnetic particle imaging (MPI) is based on the nonlinear magnetization response of magnetic nanoparticles (MNPs) around a magnetic field-free region. It uses coil detection technology to obtain the high-order harmonic components of the particle sensing signal, thereby reconstructing the concentration distribution image of the particles. MPI is an emerging functional imaging technology that only uses the contrast generated by MNPs without generating background signals during the imaging process. However, due to the lack of anatomical structure background, how to accurately locate is an important challenge for MPI small animal in vivo imaging.

[0003] Existing clinical imaging methods, such as X-ray computed tomography (X-CT), use the attenuation coefficient of X-rays after penetrating biological tissues to perform imaging, which can provide corresponding anatomical information for MPI images, thereby improving the accuracy of MNPs positioning in organisms and facilitating the observation of changes in physiological activities. Dual-mode or dual-modality imaging formed by combining two or more imaging technologies not only retains the sensitivity and high resolution of a single modality, but also realizes the complementary advantages of multiple imaging methods.

[0004] The key to achieving multimodal imaging is to place images from different times or different sources in a coordinate system for registration. In the registration process, some markers placed outside the body can be used as reference points and made to appear in images of different modes, and then these markers can be used as reference positions for automatic registration. The registration markers used for small animal MPI-CT combined imaging in current studies are all placed near the imaging site according to the experimenter's experience, with markers containing a certain amount of MNPs placed near the imaging site, making it difficult to achieve complete three-dimensional registration.

[0005] Therefore, there is a need in the art for a bimodal reference marker that can be simultaneously developed in MPI and CT modes, and the positions corresponding to the two imaging modes can be determined from the coronal plane, sagittal plane, and transverse plane, thereby forming a three-dimensional alignment device and system suitable for small animal MPI-CT combined imaging. Summary of the invention

[0006] In order to solve the above-mentioned problem in the prior art, that is, the registration marks of the existing small animal MPI-CT joint imaging are placed according to the experimenter's experience, and it is difficult to achieve complete three-dimensional registration, the present invention provides a bimodal registration device for small animal MPI-CT joint imaging, the bimodal registration device comprising a marker material, three bimodal registration marks and a support frame;

[0007] The marker materials include MPI tracers and CT contrast agents, which are used for registration marking of MPI imaging and CT imaging respectively;

[0008] Any of the bimodal registration markers comprises a glass capillary and a flexible PVC tube, wherein the glass capillary is filled with an MPI tracer, the outer layer of the glass capillary surrounds a layer of flexible PVC tube, and a CT contrast agent is filled between the outer wall of the glass capillary and the inner wall of the flexible PVC tube;

[0009] The support frame is used to fix the three double-peak registration marks, and the support frame is arranged directly above the imaging part.

[0010] In some preferred embodiments, the MPI tracer and the CT contrast agent do not affect the imaging effect of each other.

[0011] In some preferred embodiments, the bimodal registration mark further comprises a plug;

[0012] The plug is used to maintain the sealing performance between the glass capillary and the flexible PVC tube.

[0013] In some preferred embodiments, the three double-peak registration marks are inclined relative to each other and intersect at the apex of the support frame.

[0014] Another aspect of the present invention provides an automatic registration method for small animal MPI-CT combined imaging, the automatic registration method comprising:

[0015] Step S10, performing MPI projection imaging and X-CT projection imaging of the object to be imaged respectively by using the above-mentioned bimodal registration device for small animal MPI-CT combined imaging;

[0016] Step S20, based on the position of the bimodal registration mark in the imaging area, demarcating the registration area in the MPI image of MPI projection imaging and the CT image of X-CT projection imaging respectively;

[0017] Step S30, using the kmeans clustering method, classifying the pixels of the MPI image into two pixel clusters, and using the cluster centers of the two pixel clusters as registration points; using the watershed segmentation method, segmenting the boundary of the registration mark of the CT image, and using the center point within the boundary as the registration point;

[0018] Step S40, obtaining the registration point coordinates of the MPI image and the registration point coordinates of the CT image, and based on the mapping relationship between the coordinates, performing rigid registration of scaling and translation of the registration points of the MPI image of MPI projection imaging and the CT image of X-CT projection imaging, to complete the automatic registration of MPI-CT joint imaging.

[0019] In some preferred embodiments, in step S30, the pixels of the MPI image are classified into two pixel clusters by using the kmeans clustering method, and the method is:

[0020] Step S311, randomly selecting two pixel points in the registration area of ​​the MPI image as cluster centers of clustered pixels;

[0021] Step S312, calculating the Euclidean distance between all pixels other than the pixel cluster center and the pixel cluster center;

[0022] Step S313, assigning each pixel to the cluster center with the smallest distance as the initial pixel cluster, and taking the average value of all pixel values ​​in the two pixel clusters as the new cluster center;

[0023] Step S314, repeating steps S312 to S313 to adjust the position of the cluster center until the position of the cluster center does not change, and using the two cluster centers as registration points.

[0024] In some preferred embodiments, the Euclidean distance is obtained by:

[0025]

[0026] Where p represents the Euclidean distance, (x1, y1) is the coordinate of the center of the pixel cluster, and (x2, y2) is the coordinate of any pixel among all other pixels.

[0027] In some preferred embodiments, in step S30, the boundary of the registration mark of the CT image is segmented by a watershed segmentation method, and the method is:

[0028] Step S321, taking any bimodal registration marker of the CT image as a seed point;

[0029] Step S322, performing neighborhood scanning on the CT image with the seed point as the center;

[0030] Step S323, if the neighborhood pixel value is smaller than the seed point, the neighborhood pixel is used as a boundary point; otherwise, the neighborhood pixel is used as a new seed point and the original seed point is used as a boundary point;

[0031] In step S324, a group of boundary points obtained after traversing the neighborhood are respectively used as new seed points, and steps S322-S323 are repeated to traverse the entire CT image area to obtain a mask image containing a marked boundary, and the center point within the boundary is used as the registration point.

[0032] In some preferred embodiments, step S40 performs rigid registration of scaling and translation of registration points of the MPI image of MPI projection imaging and the CT image of X-CT projection imaging, and the method is:

[0033] P(x)=Ax+b

[0034] Wherein, x=(x, y, z) is the spatial position of the pixel before rigid registration, P(x) is the spatial position of the pixel after rigid registration, A is the matrix of scaling transformation, and b is the translation vector.

[0035] In some preferred embodiments, after the automatic registration of the MPI-CT combined imaging, a dual-modality image fusion step is further provided, and the method is as follows:

[0036] S f (x, y, z) = αS MPI (x,y,z)+S CT (x, y, z)

[0037] Among them, S f (x, y, z) is the gray value of the MPI-CT fusion image, S MPI (x, y, z) is the gray value of the MPI image, S CT (x, y, z) is the gray value of the corresponding CT image, x, y, z is the three-dimensional coordinate space of the image, and α is between 0 and 1, which represents the weight coefficient of the MPI image in the fused image.

[0038] Beneficial effects of the present invention:

[0039] (1) The bimodal registration device for small animal MPI-CT combined imaging of the present invention has a simple fixing device assembly and operation, which reduces the amount of tracer required for three-dimensional positioning. Through the provided bimodal marker, there is no need to replace the marker when switching imaging modes during the experiment, which reduces the experimental time and material costs. Compared with using a single MNPs as a registration marker, the bimodal marker proposed in the present invention can achieve automatic registration and avoid the complicated operation of manual adjustment.

[0040] (2) The automatic registration method for small animal MPI-CT combined imaging of the present invention directly determines the position of the region of interest through bimodal registration markers, combines artificial intelligence algorithms, and realizes three-dimensional automatic registration of MPI images and CT images with high accuracy and precision. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0042] Figure 1 It is a schematic diagram of the composition of the bimodal registration device for small animal MPI-CT combined imaging of the present invention;

[0043] Figure 2 It is a flow chart of the automatic registration method for small animal MPI-CT combined imaging of the present invention;

[0044] Figure 3 It is the image processing system architecture of one embodiment of the bimodal registration device for small animal MPI-CT combined imaging of the present invention;

[0045] Among them, 1-glass capillary, 2-flexible PVC tube, 3-support frame. DETAILED DESCRIPTION

[0046] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0047] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0048] A bimodal registration device for small animal MPI-CT combined imaging of the present invention comprises a marker material, three bimodal registration markers and a support frame;

[0049] The marker materials include MPI tracers and CT contrast agents, which are used for registration marking of MPI imaging and CT imaging respectively;

[0050] Any of the bimodal registration markers comprises a glass capillary and a flexible PVC tube, wherein the glass capillary is filled with an MPI tracer, the outer layer of the glass capillary surrounds a layer of flexible PVC tube, and a CT contrast agent is filled between the outer wall of the glass capillary and the inner wall of the flexible PVC tube;

[0051] The support frame is used to fix the three double-peak registration marks, and the support frame is arranged directly above the imaging part.

[0052] In order to more clearly explain the bimodal registration device for small animal MPI-CT combined imaging of the present invention, the following is combined with Figure 1 Each module in the embodiment of the present invention is described in detail.

[0053] The bimodal registration device for small animal MPI-CT combined imaging according to the first embodiment of the present invention comprises a marker material, three bimodal registration markers and a support frame, and each module is described in detail as follows:

[0054] The marker materials include MPI tracers and CT contrast agents, which are used for registration markers of MPI imaging and CT imaging, respectively.

[0055] The MPI tracer and the CT contrast agent do not affect the imaging effect of each other.

[0056] Any double-peak registration marker includes a glass capillary and a flexible PVC tube. The glass capillary is filled with an MPI tracer. The outer layer of the glass capillary surrounds a layer of flexible PVC tube. The space between the outer wall of the glass capillary and the inner wall of the flexible PVC tube is filled with a CT contrast agent.

[0057] The double-peak registration mark also includes a plug for maintaining the sealing of the glass capillary tube and the flexible PVC tube.

[0058] The support frame is used to fix three double-peak registration marks, and the support frame is arranged just above the imaging part.

[0059] The three double-peak registration marks are inclined relative to each other and intersect at the apex of the support frame.

[0060] In one embodiment of the present invention, the 3D imaging field of view of the two imaging modes is 6cm*12cm*6cm, the size of the small animal to be imaged is 4cm*8cm*2.5cm, and the two imaging modes share a compatible animal bed.

[0061] like Figure 1 As shown, it is a schematic diagram of the composition of the bimodal registration device for small animal MPI-CT combined imaging of the present invention, including a glass capillary 1, a flexible PVC tube 2, and a support frame 3. The support frame 3 is completed by 3D printing and can be stably placed on the animal bed along the z-axis direction of the scanner. There are grooves for placing three tubular bimodal registration marks. The size of the support frame is 5cm*11cm*5cm. From the top, front, and side of the support frame 3, the three grooves are inclined to each other.

[0062] The glass capillary has an inner diameter of 2 mm and is filled with MPI tracer. It has good sealing and is fixed in the center of the flexible PVC tube.

[0063] The flexible PVC tube has an inner diameter of 4 mm and is filled with CT contrast agent and is sealed by plugs at both ends.

[0064] There are three double-peak registration markers composed of glass capillaries and PVC tubes, which are placed in the grooves of the support frame and arranged in a relatively staggered distribution to provide accurate positioning references for the subsequent formation of three-dimensional tomographic images.

[0065] The automatic registration method for small animal MPI-CT combined imaging according to the second embodiment of the present invention is as follows: Figure 2 FIG. 1 is a flow chart of an automatic registration method for small animal MPI-CT combined imaging according to the present invention, wherein the automatic registration method comprises:

[0066] Step S10: performing MPI projection imaging and X-CT projection imaging of the object to be imaged respectively by using the above-mentioned bimodal registration device for small animal MPI-CT combined imaging.

[0067] Before performing three-dimensional MPI-CT scanning on small animals, the small animals were anesthetized, placed on a compatible animal bed, and their limbs were fixed.

[0068] Place the support frame with the bimodal registration markers on the head of the small animal so that the small animal and the three markers are all in the imaging field of view. MPI tracer and CT contrast agent are injected into the bimodal registration markers, which can perform MPI and CT imaging simultaneously, without the need to replace the markers during the complete imaging period.

[0069] Step S20: based on the position of the bimodal registration mark in the imaging area, demarcate the registration area in the MPI image of MPI projection imaging and the CT image of X-CT projection imaging.

[0070] The entire fixed registration device is placed stably on the MPI examination bed. The MPI scanner performs multi-angle two-dimensional projection imaging of the area of ​​interest and records the MPI projection image data after scanning.

[0071] Move the registration device and the animal bed, and place the fixed registration device stably on the X-CT examination bed. The CT scanner performs multi-angle two-dimensional projection imaging of the area of ​​interest and records the X-ray projection image data after scanning.

[0072] Step S30, using the kmeans clustering method, classifying the pixels of the MPI image into two pixel clusters, and using the cluster centers of the two pixel clusters as registration points; using the watershed segmentation method, segmenting the boundary of the registration mark of the CT image, and using the center point within the boundary as the registration point.

[0073] The pixels of the MPI image are classified into two pixel clusters by the kmeans clustering method, which is as follows:

[0074] Step S311, randomly selecting two pixel points in the registration area of ​​the MPI image as cluster centers of clustered pixels;

[0075] Step S312, calculating the Euclidean distance between all pixels other than the pixel cluster center and the pixel cluster center, as shown in formula (1):

[0076]

[0077] Where p represents the Euclidean distance, (x1, y1) is the coordinate of the center of the pixel cluster, and (x2, y2) is the coordinate of any pixel among all other pixels;

[0078] Step S313, assigning each pixel to the cluster center with the smallest distance as the initial pixel cluster, and taking the average value of all pixel values ​​in the two pixel clusters as the new cluster center;

[0079] Step S314, repeating steps S312 to S313 to adjust the position of the cluster center until the position of the cluster center does not change, and using the two cluster centers as registration points.

[0080] The boundary of the registration mark of the CT image is segmented by the watershed segmentation method, and the method is as follows:

[0081] Step S321, taking any bimodal registration marker of the CT image as a seed point;

[0082] Step S322, performing neighborhood scanning on the CT image with the seed point as the center;

[0083] Step S323, if the neighborhood pixel value is smaller than the seed point, the neighborhood pixel is used as a boundary point; otherwise, the neighborhood pixel is used as a new seed point and the original seed point is used as a boundary point;

[0084] In step S324, a group of boundary points obtained after traversing the neighborhood are respectively used as new seed points, and steps S322-S323 are repeated to traverse the entire CT image area to obtain a mask image containing a marked boundary, and the center point within the boundary is used as the registration point.

[0085] Step S40, obtaining the registration point coordinates of the MPI image and the registration point coordinates of the CT image, and based on the mapping relationship between the coordinates, performing rigid registration of scaling and translation of the registration points of the MPI image of MPI projection imaging and the CT image of X-CT projection imaging, to complete the automatic registration of MPI-CT joint imaging.

[0086] The rigid registration of the scaling and translation of the registration points of the MPI image of MPI projection imaging and the CT image of X-CT projection imaging is performed as shown in formula (2):

[0087] P(x)=Ax+b (2)

[0088] Wherein, x=(x, y, z) is the spatial position of the pixel before rigid registration, P(x) is the spatial position of the pixel after rigid registration, A is the matrix of scaling transformation, and b is the translation vector.

[0089] After the automatic registration of MPI-CT combined imaging, a dual-modality image fusion step is also provided, and the method is as follows:

[0090] The MPI image is mapped in pseudo color according to the color scheme, while the CT image is a grayscale image with a scale of 0 to 255. The mapping, window width and window position can be adjusted according to the specific situation. The 3DMed image fusion display module is used to display the fused image after registration.

[0091] The weighted average fusion method is used to assign different weights to images of different modalities, and the images of the two modalities are fused according to the weights, as shown in formula (3):

[0092] S f (x, y, z) = αS MPI (x,y,z)+S CT (x, y, z) (3)

[0093] Among them, S f (x, y, z) is the gray value of the MPI-CT fusion image, S MPI (x, y, z) is the gray value of the MPI image, S CT (x, y, z) is the gray value of the corresponding CT image, x, y, z is the three-dimensional coordinate space of the image, and α is between 0 and 1, which represents the weight coefficient of the MPI image in the fused image.

[0094] α is a transparency coefficient greater than 0 and less than 1, which can be adjusted according to specific circumstances, and the present invention will not be described in detail here.

[0095] The automatic registration system of the small animal MPI-CT combined imaging device according to the third embodiment of the present invention is as follows: Figure 3 As shown, the image processing system architecture of an embodiment of the bimodal registration device for small animal MPI-CT joint imaging of the present invention is shown. The automatic registration system includes an image reading unit, a resampling unit, a MITK image reconstruction module, a dual-modal image automatic registration module, an interactive operation unit, a quantitative analysis module and a 3DMed image fusion display module:

[0096] The image reading unit is connected to the image resampling unit, reads in the original data information of the image and performs resampling.

[0097] The image resampling unit is connected to the MITK 3D image reconstruction module and transmits data. The MITK 3D image reconstruction module is used to reconstruct the MPI projection image and X-ray projection image data into a 3D tomographic image. The tomographic images are spliced ​​together to display the coronal plane, sagittal plane and transverse section of the region of interest respectively.

[0098] The 3D image reconstruction module of MITK adopts the reconstruction algorithm of filtered back projection, performs one-dimensional Fourier transform on the projections at multiple angles and multiplies them by the filtering function; performs direct back projection on the projection function after the Fourier inverse transform; changes the angle until the back projection at all 180° is completed; performs 3D tomographic reconstruction on the MPI projection data and X-ray projection data, and the reconstruction of the X-ray projection data becomes a CT image; the MPI image and the CT image are saved as tomographic images of the sagittal plane, coronal plane and cross section, respectively.

[0099] The MITK image reconstruction module is connected to the dual-modality image automatic registration module, and the data information of the dual modality after registration is displayed through the 3DMed image fusion display module. The automatic registration module can automatically distinguish the registration area and the region of interest, run the clustering-based recognition algorithm and the marker-based watershed segmentation algorithm, and intelligently identify the position of the registration point on the MPI and CT images respectively. The registration point is used as the reference point for rigid registration. During the registration, the CT image is used as the background image and the MPI image is used as the floating image. The interactive operation unit is used to manually assist in the calibration of the position of the seed point in the watershed algorithm.

[0100] The quantitative analysis module is connected to the fusion display system and calls the interactive operation unit to draw the ROI.

[0101] The MPI image is mapped in pseudo color according to the color scheme, while the CT image is a grayscale image with a scale of 0 to 255. The mapping, window width and window position can be adjusted according to the specific situation. The 3DMed image fusion display module is used to display the fused image after registration.

[0102] The quantitative analysis module includes region of interest (ROI) delineation and linear calibration. The user interactively draws a set of regions of interest on the registered CT tomographic image, and then imports the mask image of the region of interest into the registered MPI image. The linear calibration process is the method for MPI to achieve quantification. Since there is a linear relationship between the intensity of the MPI signal and the MNPs content, the MNPs content in the ROI can be estimated by obtaining the ratio between the known MNPs content in the marker and the MPI signal.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process and related instructions of the method described above can refer to the corresponding process in the aforementioned system embodiment, and will not be repeated here.

[0104] It should be noted that the bimodal registration device and automatic registration system and automatic registration method for small animal MPI-CT joint imaging provided in the above embodiments are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiments can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.

[0105] A device according to a fourth embodiment of the present invention includes:

[0106] at least one processor; and

[0107] a memory communicatively connected to at least one of the processors; wherein,

[0108] The memory stores instructions that can be executed by the processor, and the instructions are used to be executed by the processor to implement the above-mentioned automatic registration method for small animal MPI-CT combined imaging.

[0109] A fifth embodiment of the present invention is a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to be executed by the computer to implement the above-mentioned automatic registration method for small animal MPI-CT combined imaging.

[0110] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process and related instructions of the storage device and processing device described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0111] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the technical field. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0112] The terms "first", "second", etc. are used to distinguish similar objects rather than to describe or indicate a particular order or sequence.

[0113] The term "comprise" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that includes a list of elements includes not only those elements but also other elements not expressly listed, or also includes elements inherent to such process, method, article, or apparatus / device.

[0114] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An automatic registration method for small animal MPI-CT combined imaging, characterized in that: A bimodal registration device based on small animal MPI-CT joint imaging is implemented, and the registration device includes: marker material, three bimodal registration markers, and a support frame; The marker materials include MPI tracers and CT contrast agents, which are used for registration marking of MPI imaging and CT imaging respectively; Any of the bimodal registration markers comprises a glass capillary and a flexible PVC tube, wherein the glass capillary is filled with an MPI tracer, the outer layer of the glass capillary surrounds a layer of flexible PVC tube, and a CT contrast agent is filled between the outer wall of the glass capillary and the inner wall of the flexible PVC tube; The support frame is used to fix the three double-peak registration marks, and the support frame is arranged just above the imaging part; The automatic registration method comprises: Step S10, performing MPI projection imaging and X-CT projection imaging of the object to be imaged respectively; Step S20, based on the position of the bimodal registration mark in the imaging area, demarcating the registration area in the MPI image of MPI projection imaging and the CT image of X-CT projection imaging respectively; Step S30, using the kmeans clustering method, classifying the pixels of the MPI image into two pixel clusters, and using the cluster centers of the two pixel clusters as registration points; using the watershed segmentation method, segmenting the boundary of the registration mark of the CT image, and using the center point within the boundary as the registration point; Step S40, obtaining the registration point coordinates of the MPI image and the registration point coordinates of the CT image, and based on the mapping relationship between the coordinates, performing rigid registration of scaling and translation of the registration points of the MPI image of MPI projection imaging and the CT image of X-CT projection imaging, to complete the automatic registration of MPI-CT joint imaging.

2. The automatic registration method for small animal MPI-CT combined imaging according to claim 1, characterized in that: The MPI tracer and the CT contrast agent do not affect the imaging effect of each other.

3. The automatic registration method for small animal MPI-CT combined imaging according to claim 1, characterized in that: The bimodal registration marker also includes a plug; The plug is used to maintain the sealing performance between the glass capillary and the flexible PVC tube.

4. The automatic registration method for small animal MPI-CT combined imaging according to claim 1, characterized in that: The three double-peak registration marks are inclined with respect to each other and intersect at the apex of the support frame.

5. The automatic registration method for small animal MPI-CT combined imaging according to any one of claims 1 to 4, characterized in that: In step S30, the pixels of the MPI image are classified into two pixel clusters by using the kmeans clustering method, and the method is as follows: Step S311, randomly selecting two pixel points in the registration area of ​​the MPI image as cluster centers of clustered pixels; Step S312, calculating the Euclidean distance between all pixels other than the pixel cluster center and the pixel cluster center; Step S313, assigning each pixel to the cluster center with the smallest distance as the initial pixel cluster, and taking the average value of all pixel values ​​in the two pixel clusters as the new cluster center; Step S314, repeating steps S312 to S313 to adjust the position of the cluster center until the position of the cluster center does not change, and using the two cluster centers as registration points.

6. The automatic registration method for small animal MPI-CT combined imaging according to claim 5, characterized in that: The Euclidean distance is obtained by: Among them, p represents the Euclidean distance, (x1, y1) is the coordinate of the center of the pixel cluster, and (x2, y2) is the coordinate of any pixel among all other pixels.

7. The automatic registration method for small animal MPI-CT combined imaging according to any one of claims 1 to 4, characterized in that: In step S30, the boundary of the registration mark of the CT image is segmented by a watershed segmentation method, and the method is as follows: Step S321, taking any bimodal registration marker of the CT image as a seed point; Step S322, performing neighborhood scanning on the CT image with the seed point as the center; Step S323, if the neighborhood pixel value is smaller than the seed point, the neighborhood pixel is used as a boundary point; Otherwise, the neighborhood pixels are used as new seed points and the original seed points are used as boundary points; In step S324, a group of boundary points obtained after traversing the neighborhood are respectively used as new seed points, and steps S322-S323 are repeated to traverse the entire CT image area to obtain a mask image containing a marked boundary, and the center point within the boundary is used as the registration point.

8. The automatic registration method for small animal MPI-CT combined imaging according to any one of claims 1 to 4, characterized in that: In step S40, the rigid registration of scaling and translation of the registration points of the MPI image of the MPI projection imaging and the CT image of the X-CT projection imaging is performed, and the method is as follows: P(x)=Ax+b Among them, x = (x, y, z) is the spatial position of the pixel before rigid registration, P (x) is the spatial position of the pixel after rigid registration, A is the matrix of scaling transformation, and b is the translation vector.

9. The automatic registration method for small animal MPI-CT combined imaging according to any one of claims 1 to 4, characterized in that: After the automatic registration of the MPI-CT combined imaging, a dual-modality image fusion step is also provided, and the method is as follows: S f (x,y,z)=αS MPI (x,y,z)+S CT (x,y,z) Among them, S f (x, y, z) is the gray value of the MPI-CT fusion image, S MPI (x, y, z) is the gray value of the MPI image, S CT (x, y, z) is the gray value of the corresponding CT image, x, y, z is the three-dimensional coordinate space of the image, and α is between 0 and 1, which represents the weight coefficient of the MPI image in the fused image.

Images