CN113066113B - Method and equipment for constructing spontaneous hypertensive rat brain template and map set - Google Patents
Method and equipment for constructing spontaneous hypertensive rat brain template and map set Download PDFInfo
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Abstract
The invention discloses a construction method of a spontaneous hypertension rat brain template and a map set and related equipment, wherein the construction method of the spontaneous hypertension rat brain template utilizes a magnetic resonance brain image of a spontaneous hypertension rat to construct the brain template, and the obtained brain template can better realize the accurate registration of the magnetic resonance brain image of the spontaneous hypertension rat and is convenient for realizing the analysis of the brain image data of the spontaneous hypertension rat; the map set obtained by the construction method of the map set of the spontaneous hypertensive rat can realize accurate positioning and brain region extraction of brain tissues of the spontaneous hypertensive rat and provide a basis for construction of a structural or functional network map in a whole brain range.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to a construction method of a spontaneous hypertension rat brain template, a construction method of a spontaneous hypertension rat map set, electronic equipment and a computer readable storage medium.
Background
With the development of aging population, the health level and the quality of life of the aged population are severely restricted by body injury and various complications caused by hypertension, and a large amount of medical and social resources are consumed. The number of hypertension patients is greatly increased globally, and high attention is paid to the prevention and management of hypertension. The influence of the hypertension on the brain aging process is known and understood, and important basis can be provided for early prevention, early diagnosis, early intervention and early treatment of the hypertension. Clinical studies on the human body have difficulty in controlling various confounding factors (such as drug therapy, lifestyle, diet, obesity, etc.) of a subject, and since most clinical studies are cross-sectional studies, it is difficult to exclude interference of individual differences. Therefore, animal experiments have irreplaceable effects in the study of the influence of hypertension on the brain aging process.
The growth cycle of the rat is relatively short, and longitudinal research can be carried out to reduce individual difference and reduce the number of the tested rats to a certain extent. Spontaneous Hypertensive Rats (SHR) are the most widely used animal models of human essential hypertension at present, similar to hypertensive population, and SHR is accompanied by significant brain atrophy, atherosclerosis and heart failure, and is responsive to hypotensive drugs. The noninvasive magnetic resonance imaging technology provides a powerful means for the research of rat brain, and can evaluate the structure and functional characteristics of the rat brain. Standard brain templates and atlas are indispensable tools for analyzing neuroimaging data. Although SHR has been used in research for nearly 60 years, no systematic report on SHR standard brain templates is currently available. Although there are currently many brain templates based on healthy rats, the significant structural differences make normal rat templates unsuitable for SHR due to the marked expansion of the SHR ventricular system. If the healthy rat brain standard template is forcibly adopted to carry out spatial transformation on the individual SHR brain image, the registration precision of the image can be influenced, anatomical position positioning deviation is caused, and the generated error can influence the research conclusion. Therefore, a set of brain templates of spontaneous hypertensive rats is urgently needed.
Disclosure of Invention
In view of the above problems, the present invention provides a method for constructing a brain template of a spontaneously hypertensive rat, a method for constructing a map set of a spontaneously hypertensive rat, an electronic device, and a computer-readable storage medium.
The invention provides a method for constructing a spontaneous hypertensive rat brain template, which comprises the following steps:
receiving magnetic resonance brain images of a plurality of spontaneously hypertensive rats, the magnetic resonance brain images of each spontaneously hypertensive rat comprising a T2 weighted magnetic resonance brain image;
pre-processing the T2 weighted magnetic resonance brain image of each spontaneously hypertensive rat, said pre-processing including the ablation of non-brain tissue;
turning the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertension rat left and right to obtain a T2 weighted magnetic resonance turned brain image of each corresponding spontaneous hypertension rat;
receiving a first reference template selection instruction, and selecting a preprocessed T2 weighted magnetic resonance brain image indicated by the first reference template selection instruction as a first reference template;
repeatedly iterating by using all preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template through methods of spatial registration, image averaging and residual error calculation to obtain a first average image;
turning the first average image left and right to obtain a first average turned image, and carrying out image averaging on the first average image and the first average turned image to obtain a second reference template; and
and repeatedly iterating by using all the preprocessed T2 weighted magnetic resonance brain images, all the preprocessed T2 weighted magnetic resonance reversed brain images and the second reference template through methods of spatial registration, image averaging, mean image reversal re-averaging and residual error calculation to obtain a T2 standard template.
In one embodiment, the construction method further comprises:
carrying out target brain tissue segmentation on the T2 standard template to obtain a first target brain tissue probability map, wherein the target brain tissue comprises: gray matter, white matter and cerebrospinal fluid;
turning the first target brain tissue probability map left and right to obtain a corresponding first target brain tissue probability turning map;
carrying out image averaging on the first target brain tissue probability map and the first target brain tissue probability inversion map to obtain a target brain tissue initial probability map; and
and (3) utilizing the initial probability map of the target brain tissue and the T2 standard template to repeatedly iterate each preprocessed T2 weighted magnetic resonance brain image and each preprocessed T2 weighted magnetic resonance inverted brain image by means of spatial registration, tissue segmentation, image averaging, image inversion re-averaging and residual error calculation to obtain the probability map of the target brain tissue.
In one embodiment, the magnetic resonance brain image of each spontaneously hypertensive rat comprises a diffusion tensor magnetic resonance image;
the construction method further comprises the following steps:
respectively carrying out binarization processing on the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map to obtain a gray matter tissue mask, a white matter tissue mask and a cerebrospinal fluid tissue mask;
preprocessing all the diffusion tensor magnetic resonance images to obtain a plurality of diffusion parameter graphs corresponding to each diffusion tensor magnetic resonance image;
turning each diffusion parameter graph left and right respectively to obtain a diffusion parameter turning graph corresponding to each diffusion parameter graph respectively;
registering each diffusion parameter map and the corresponding diffusion parameter flip map to the T2 standard template respectively;
carrying out image averaging on the registered diffusion parameter graphs of the same kind and the corresponding registered diffusion parameter overturning graphs, and overturning and then averaging the average images to obtain a diffusion parameter initial template corresponding to each kind of diffusion parameter graphs;
repeatedly iterating by using the same kind of diffusion parameter images, the corresponding diffusion parameter overturning images and the corresponding diffusion parameter initial templates through image averaging, spatial registration, image averaging, average image overturning re-averaging and residual error calculation methods to obtain the diffusion parameter templates corresponding to each kind of diffusion parameter images; and
and stripping non-brain tissue from the dispersion parameter template corresponding to each dispersion parameter map by using the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask to obtain the dispersion parameter standard template corresponding to each dispersion parameter map.
In one embodiment, the diffusion parameter map comprises an FA map, an MD map and a b0 map, and the FA map, the MD map and the b0 map correspond to a standard template which is an FA standard template, an MD standard template and a b0 standard template respectively.
In one embodiment, the magnetic resonance brain image of each spontaneously hypertensive rat comprises a functional magnetic resonance image;
the construction method further comprises the following steps:
respectively carrying out binarization processing on the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map to obtain a gray matter tissue mask, a white matter tissue mask and a cerebrospinal fluid tissue mask;
preprocessing the functional magnetic resonance image of each spontaneous hypertension rat to obtain a first functional magnetic resonance image;
turning all the first functional magnetic resonance images left and right to obtain first functional magnetic resonance turned images;
registering all the first functional magnetic resonance images and all the first functional magnetic resonance flip images to the T2 standard template to obtain standardized first functional magnetic resonance images and standardized first functional magnetic resonance flip images;
carrying out image averaging on all the standardized first functional magnetic resonance images and the standardized first functional magnetic resonance overturning images, overturning and averaging the average images, and obtaining a functional magnetic resonance image initial template;
repeatedly iterating all the first functional magnetic resonance images, all the first functional magnetic resonance overturning images and the functional magnetic resonance image initial template through methods of space registration, image averaging, averaging image overturning and averaging again and residual error calculation to obtain a functional magnetic resonance image template; and
and stripping non-brain tissues of the functional magnetic resonance image template by using the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask to obtain a functional magnetic resonance image standard template.
In one embodiment, the functional magnetic resonance image comprises an EPI image and the functional magnetic resonance image standard template comprises an EPI standard template.
In another aspect of the present invention, a method for constructing a map set of spontaneously hypertensive rats is further provided, which comprises:
acquiring a first transformation relation of registering the Tohoku T2 template to the T2 standard template obtained by the construction method;
transforming the Tohoku map set according to the first transformation relation to obtain a target right cortex structure;
on the basis of the target right cortical structure, respectively referring to the T2 standard template obtained by the construction method, the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map obtained by the construction method, and the dispersion parameter standard template obtained by the construction method, drawing the target right subcortical structure at the coronal level and correcting at the axial level and the sagittal level;
performing image calculation on the target right cortex structure to obtain a target left cortex structure which is symmetrical to the target right cortex structure; and
performing image calculation on the target right-side subcortical structure to obtain a target left-side subcortical structure which is symmetrical to the target right-side subcortical structure;
wherein the target right-side cortical structure, target left-side cortical structure, target right-side sub-cortical structure, and target left-side sub-cortical structure comprise the map set of spontaneously hypertensive rats.
In one embodiment, the target right cortical structure comprises a plurality of right cortical brain regions, and the target left cortical structure comprises a plurality of left cortical brain regions, wherein each right cortical brain region corresponds to one left cortical brain region in a mirror image, and each right cortical brain region and each left cortical brain region correspond to one label; the target right sub-cortical structure comprises a plurality of first right sub-cortical sub-brain regions and a plurality of second right sub-cortical sub-brain regions, and the target left sub-cortical sub-structure comprises a plurality of first left sub-cortical sub-brain regions and a plurality of second left sub-cortical sub-brain regions; each first right subcortical brain region is a complete brain region and corresponds to a first left subcortical brain region in a mirror image manner; each second right subcortical brain region is a half brain region and corresponds to a second left subcortical brain region in a mirror image manner to form a complete brain region; each first right-side subcortical brain region and each first left-side subcortical brain region respectively correspond to one label, and each second right-side subcortical brain region and the corresponding second left-side subcortical brain region jointly correspond to one label; each of which is different from the others.
In another aspect of the present invention, an electronic device is further provided, including:
one or more processors;
a memory;
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the construction method described above.
In another aspect of the present invention, a computer-readable storage medium is further provided, on which a computer program is stored, and the computer program is executed by a processor to implement the above-mentioned construction method.
According to the construction method of the spontaneous hypertension rat brain template, the brain template is constructed by using the magnetic resonance brain image of the spontaneous hypertension rat, and the obtained brain template can better realize accurate registration of the magnetic resonance brain image of the spontaneous hypertension rat, so that the analysis of the brain image data of the spontaneous hypertension rat is facilitated; according to the map set obtained by the construction method of the map set of the spontaneous hypertensive rat in the embodiment of the invention, the accurate positioning and brain region extraction of the brain tissue of the spontaneous hypertensive rat can be realized, and a basis is provided for the construction of a structural or functional network map in the whole brain range. Further, because the brain template and the atlas obtained by the method in the embodiment of the invention are symmetrical, the obtained brain template and atlas can be used for researching different brain differences.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 shows a flowchart of a method for constructing a spontaneous hypertensive rat brain template according to an embodiment of the present invention.
Fig. 2 shows a flowchart of a method for constructing a spontaneous hypertensive rat brain template according to an embodiment of the present invention.
Fig. 3 shows a flowchart of a method for constructing a spontaneous hypertensive rat brain template according to an embodiment of the present invention. Fig. 4 shows a flowchart of a method for constructing a spontaneous hypertensive rat brain template according to an embodiment of the present invention.
Fig. 5 shows a flowchart of a method for constructing a spontaneous hypertensive rat brain template according to an embodiment of the present invention.
Fig. 6 shows a block diagram of an electronic device according to an embodiment of the invention.
Fig. 7 shows a block diagram of an electronic device in an embodiment in accordance with the invention.
Fig. 8 is a diagram showing an internal structure of a computer apparatus according to another embodiment of the present invention.
FIG. 9 shows sections of spontaneous hypertensive rat T2 standard template, FA standard template, MD standard template, b0 standard template, and EPI standard template at coronal, axial, and sagittal positions, according to the experimental example obtained in the present invention.
Fig. 10 shows slices of the gray matter tissue probability map, the white matter tissue probability map, the cerebrospinal fluid tissue probability map, and the pseudo-color tissue probability map superimposed on the T2 standard template image at the coronal, axial, and sagittal positions of the spontaneously hypertensive rat obtained in the experimental example of the present invention according to the present invention.
FIG. 11 shows a map set of spontaneously hypertensive rats obtained in an experimental example according to the present invention.
Fig. 12 shows a graph of the similarity coefficient (DICE), Hausdorff Distance (HD) results comparing individual space T2WI images with brain template space in experimental examples of the present invention at gray matter, white matter, cerebrospinal fluid, and whole brain levels.
Fig. 13 is a graph showing the results of comparison of the volume values of gray matter, white matter, cerebrospinal fluid and whole brain in the individual space and the brain template space in the experimental example of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
In some of the flows described in the present specification and claims and in the above figures, a number of operations are included that occur in a particular order, but it should be clearly understood that these operations may be performed out of order or in parallel as they occur herein, with the order of the operations being indicated as 101, 102, etc. merely to distinguish between the various operations, and the order of the operations by themselves does not represent any order of performance. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, terms, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In an embodiment, as shown in fig. 1, a method for constructing a spontaneous hypertensive rat brain template is provided, and this embodiment is illustrated by applying the method to a terminal, it is to be understood that the method may also be applied to a server, and may also be applied to a system including the terminal and the server, and is implemented by interaction between the terminal and the server. The method for constructing the spontaneous hypertensive rat brain template in the embodiment comprises the following steps:
In the embodiment of the invention, the magnetic resonance brain image is obtained by performing whole brain scan on the spontaneous hypertensive rat, wherein the T2 weighted magnetic resonance brain image is obtained by performing T2WI scan on the spontaneous hypertensive rat.
Preferably, in an embodiment, the receiving the magnetic resonance brain images of the plurality of spontaneous hypertensive rats includes receiving magnetic resonance brain images obtained by scanning the plurality of spontaneous hypertensive rats at a plurality of time points after adulthood; the magnetic resonance brain image of each spontaneously hypertensive rat comprises a plurality of T2 weighted magnetic resonance brain images corresponding to a plurality of time points.
For example, the T2 weighted mrgs of multiple spontaneously hypertensive rats may be obtained by scanning 8 spontaneously hypertensive rats at 3 time points (10 weeks, 24 weeks, and 52 weeks), so that there are actually 24T 2 weighted mrgs, and the 1T 2 weighted mrgs in this embodiment of the present invention actually refers to a set of images including multiple frames, and all the following operations on the 1T 2 weighted mrgs are performed on the corresponding images of each frame. The selection of multiple time points allows the resulting magnetic resonance images to run through early adulthood and elderly in spontaneously hypertensive rats, thus allowing the resulting brain template to be suitable for the processing of spontaneously hypertensive rat brain images over a longer time span.
The T2 weighted magnetic resonance brain image of each spontaneously hypertensive rat is preprocessed, step 102, including the ablation of non-brain tissue.
In the embodiment of the invention, the stripping of the non-brain tissue can reduce the processing range of the image, reduce the processing amount and save the processing time. For example, the non-brain tissue may be stripped off manually using ITK-SNAP (version 3.6.0), for example.
In some embodiments, the preprocessing further includes performing bias field correction on the T2 weighted magnetic resonance brain image prior to ablation of non-brain tissue. For example, the N4 algorithm may be used to perform a bias field correction on the T2 weighted magnetic resonance brain image. In some embodiments, the preprocessing further includes voxel up-scaling the T2 weighted magnetic resonance brain image to a preset multiple prior to non-brain tissue ablation. In a specific embodiment, the preset multiple is 10 times. The effect of the voxel-magnifying pre-processing is to make the size of the brain image of spontaneously hypertensive rats adaptable to conventional human-developed image data processing software, such as SPM12 (version 2013 b).
And 103, performing left-right flipping on the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertension rat to obtain a T2 weighted magnetic resonance flipped brain image of each corresponding spontaneous hypertension rat.
In the embodiment of the invention, the T2 weighted magnetic resonance flip brain image of each corresponding spontaneous hypertension rat is obtained by flipping the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertension rat left and right; the T2 weighted magnetic resonance flip brain image and the preprocessed T2 weighted magnetic resonance brain image are used as original images in a subsequent processing process, so that the number of the original images is doubled, and the sample size is expanded to optimize the finally obtained T2 standard template to a certain degree; furthermore, the T2 standard template obtained subsequently is a symmetrical brain template by obtaining a T2 weighted magnetic resonance flip brain image, so that the method can be better suitable for the study of difference of the brain side.
For example, 24T 2 weighted mr brain images obtained by scanning 8 spontaneous hypertensive rats at 3 time points (10 weeks, 24 weeks, and 52 weeks) and 24T 2 weighted mr brain images obtained by left-right flipping each other are 24T 2 weighted mr flipped brain images.
In the embodiment of the present invention, the designated spontaneous hypertensive rat carried by the first reference template selecting instruction generally refers to the spontaneous hypertensive rat corresponding to the T2 weighted magnetic resonance brain image in which the brain tissue is located at the center of the image and the brain tissue has good bilateral symmetry, in the T2 weighted magnetic resonance brain image of all the spontaneous hypertensive rats.
Preferably, when the magnetic resonance brain image of each spontaneously hypertensive rat includes a plurality of T2 weighted magnetic resonance brain images corresponding to a plurality of time points, the pre-processed T2 weighted magnetic resonance brain image of the specified spontaneously hypertensive rat carried by the first reference template selection instruction is used as the first reference template, specifically, the pre-processed T2 weighted magnetic resonance brain image of the specified spontaneously hypertensive rat carried by the first reference template selection instruction corresponding to an intermediate time point is used as the first reference template, wherein the brain tissue in the processed T2 weighted magnetic resonance brain image as the first reference template is located at the center of the image, and the bilateral symmetry of the brain tissue is good.
For example, 24T 2 weighted magnetic resonance brain images obtained by scanning 8 spontaneous hypertensive rats at 3 time points (10 weeks, 24 weeks and 52 weeks) are preferably selected as the first reference template, wherein the brain tissue in the T2 weighted magnetic resonance brain image of the 24-week spontaneous hypertensive rats is located at the center of the image, and the image with good bilateral symmetry of the brain tissue is used as the first reference template.
And 105, repeatedly iterating by using all preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template through methods of spatial registration, image averaging and residual error calculation to obtain a first average image.
In an embodiment of the present invention, the repeatedly iterating the method of spatial registration, image averaging and residual calculation by using all the preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template to obtain the first average image specifically includes:
step 1051, registering all preprocessed T2 weighted magnetic resonance brain images except the first reference template to the first reference template, and performing image averaging on all registered T2 weighted magnetic resonance brain images to obtain a first initial average image;
step 1052, calculating a residual between the first initial average image and the first reference template, and if the residual is smaller than a first predetermined value, accepting the first initial average image as a first average image;
step 1053, if the residual is greater than or equal to the first predetermined value, the initial average image is used as a new first reference template, and step 1051 (at this time, all the preprocessed T2 weighted magnetic resonance brain images need to be processed in step 1051) and step 1052 are repeated until the residual is less than the first predetermined value, so as to obtain the first average image.
In the embodiment of the present invention, the preferred spatial registration is registration by using an image intensity registration-based method. In particular, wherein "all pre-processed T2 weighted magnetic resonance brain images except the first reference template are registered to the first reference template respectively" is specifically registered using a combination of 12-parameter affine transformation (12-parameter after transformation) and non-linear transformation (non-linear registration). The 12-parameter affine transformation performs transformation such as rotation, translation and stretching deformation on the image; the nonlinear transformation is a local fine difference between the 12-parameter affine transformed image and the template.
In the present embodiment, the residual refers to the intensity residual average difference (i.e., RSID). The residual error is calculated as follows:
wherein imgi represents a first reference template, imgm represents an initial average image, i, j, k represents matrix coordinates of pixel points in the image, and n represents the total number of pixel points in the image.
And 106, turning the first average image left and right to obtain a first average turned image, and carrying out image averaging on the first average image and the first average turned image to obtain a second reference template.
And 107, repeatedly iterating by using all the preprocessed T2 weighted magnetic resonance brain images, all the preprocessed T2 weighted magnetic resonance reversed brain images and the second reference template through methods of spatial registration, image averaging, image reversal re-averaging and residual error calculation to obtain a T2 standard template.
In an embodiment of the present invention, the repeatedly iterating the method of spatial registration, image averaging, mean image inversion re-averaging, and residual calculation by using all preprocessed T2 weighted magnetic resonance brain images, all T2 weighted magnetic resonance inverted brain images, and the second reference template to obtain the T2 standard template specifically includes:
step 1071, registering all preprocessed T2 weighted magnetic resonance brain images and all T2 weighted magnetic resonance flip brain images to the second reference template, and performing image averaging on all registered T2 weighted magnetic resonance brain images and all registered T2 weighted magnetic resonance flip brain images to obtain a second initial average image;
step 1072, left-right turning the second average image to obtain a second average turned image, and performing image averaging on the second average image and the second average turned image to obtain a third reference template.
Step 1073, calculating a residual error between the third reference template and the second reference template, and if the residual error is smaller than a second predetermined value, accepting the third reference template as a T2 standard template;
step 1074, if the residual error is greater than or equal to the second predetermined value, taking the third reference template as a new reference template, and repeating the steps 1071, 1072 and 1073 until the residual error is less than the second predetermined value, thereby obtaining the T2 standard template.
In the embodiment of the present invention, the second reference template obtained in step 106 is obtained by averaging the images of the first averaged image and the first averaged flipped image, so that the second reference template itself is a symmetric image. In step 107, since all the preprocessed T2 weighted magnetic resonance brain images and all the T2 weighted magnetic resonance flipped brain images are registered to the second reference template, then image averaging is performed, the averaged images are flipped and averaged to obtain a third reference template, residual calculation is performed on the third reference template and the second reference template, and iteration is repeated until the residual is smaller than a second predetermined value. The self-symmetry of the second reference template obtained in step 106 and the image averaging of the registered images of all the preprocessed T2 weighted mr brain images and all the T2 weighted mr flip brain images in step 107 are performed, and the averaged images are flipped and averaged, so that the finally obtained images have good symmetry. Therefore, the dual functions of step 106 and step 107 make the finally obtained T2 standard template have better left-right symmetry.
In some embodiments, the T2 standard template may be oversampled to 1mm equivalent voxel (after 10 times voxel magnification), and the image origin of the T2 standard template may be adjusted to obtain an equivalent voxel T2 standard template. In the embodiment of the invention, each voxel in the isosomal T2 standard template is a small cube, so that the image has a better visualization effect on each slice in coronal, axial and sagittal positions, and the calculation of the subsequent image post-processing is facilitated. The adjusting of the image origin of the T2 standard template comprises: and acquiring the origin coordinate position of the Tohoku T2 template, and readjusting the origin of the T2 standard template according to the origin coordinate position of the Tohoku T2 template. After the image origin of the T2 standard template is adjusted, the coordinates of the image origin are well identified, and the registration of the individual space image to the template space is facilitated. The process in which the origin is adjusted may be performed using the SPM12 toolkit.
The T2 standard template obtained by the method shown in FIG. 1 is one of the brain templates, and other types of brain template construction methods are also disclosed in other embodiments of the present invention. FIG. 2 is another embodiment of the present invention, which is a method for constructing a brain template of a spontaneously hypertensive rat. As shown in fig. 2, the brain template obtained in this embodiment is a brain tissue probability map, and the number of the brain tissue probability maps obtained finally is three, which are a gray matter probability map, a white matter probability map, and a cerebrospinal fluid probability map. As shown in fig. 2, the method for constructing the spontaneous hypertensive rat brain template in this embodiment further includes the following steps:
In this embodiment, step 201 obtains a preliminary segmentation target brain tissue probability map by performing a preliminary segmentation on the T2 standard template; then, the preliminary segmentation target brain tissue probability map is used as a prior template, and the T2 standard template is segmented again to obtain a first target brain tissue probability map; the target brain tissue includes: gray matter, white matter and cerebrospinal fluid.
In a more specific embodiment, step 201 includes the steps of:
carrying out primary segmentation on the T2 standard template by using a FAST toolkit of FSL to obtain a primary segmentation target brain tissue probability map, wherein the target brain tissue comprises: gray matter, white matter and cerebrospinal fluid;
correcting the preliminary target brain tissue probability map by using ITK-SNAP software;
and taking the corrected preliminary segmentation target brain tissue probability map as a prior template, and performing tissue segmentation on the T2 standard template by using a SPM (Linear mixture Per second) unified segmentation algorithm to obtain a first target brain tissue probability map.
In one embodiment, the correcting the preliminary segmentation target brain tissue probability map by using the ITK-SNAP software is a method to be adopted when an image obtained by preliminary segmentation of the T2 standard template by using the FAST toolkit of FSL is defective, and specifically includes: and carrying out binarization processing on the preliminary segmentation target brain tissue probability map by using ITK-SNAP software to obtain a corrected preliminary segmentation target brain tissue probability map. Specifically, because some points may be displayed incorrectly on the preliminary segmentation target brain tissue probability map, for example, a gap may occur in the middle part of the tissue, the picture is corrected by using a binarization method, so that there are no obvious errors and unreasonable pixels in the prior template for performing tissue segmentation on the T2 standard template by using the SPM unified segmentation algorithm, and the accuracy of subsequent segmentation is ensured.
And 202, turning the first target brain tissue probability map left and right to obtain a corresponding first target brain tissue probability turning map.
And 204, repeatedly iterating each preprocessed T2 weighted magnetic resonance brain image and each preprocessed T2 weighted magnetic resonance inverted brain image by using the target brain tissue initial probability map and a T2 standard template through methods of spatial registration, tissue segmentation, image averaging, average image inversion re-averaging and residual error calculation to obtain the target brain tissue probability map.
In the embodiment of the invention, the target brain tissue probability map is obtained by repeatedly iterating each preprocessed T2 weighted magnetic resonance brain image and each preprocessed T2 weighted magnetic resonance flipped brain image through methods of spatial registration, tissue segmentation, image averaging, image flipping re-averaging and residual error calculation by using the target brain tissue initial probability map and a T2 standard template; the method specifically comprises the following steps:
step 2041, registering each preprocessed T2 weighted mr brain image and each T2 weighted mr flip brain image to a T2 standard template, respectively.
And 2042, performing brain tissue segmentation on each preprocessed T2 weighted magnetic resonance brain image and each T2 weighted magnetic resonance overturn brain image to obtain a corresponding target brain tissue probability map by using the target brain tissue initial probability map.
Step 2043, performing image averaging on all the segmented target brain tissue probability maps respectively to obtain a target brain tissue probability average map.
Step 2044, the target brain tissue probability average map is inverted left and right to obtain an inverted image of the target brain tissue probability average map, and the inverted images of the target brain tissue probability average map and the target brain tissue probability average map are subjected to image averaging to obtain a symmetric target brain tissue probability average map.
Step 2045, calculating a residual error between the symmetric target brain tissue probability average map and the brain tissue initial probability map, and if the residual error is smaller than a third preset value, receiving the symmetric target brain tissue probability average map as a target brain tissue probability map.
And if the residual error is larger than or equal to a third preset value, taking the average graph of the symmetrical target brain tissue probability graphs as a new target brain tissue initial probability graph, and repeating the steps 2041 to 2045 until the residual error is smaller than the third preset value to obtain a target brain tissue probability graph. In one embodiment, a residual is calculated in step 2045 for the symmetric target brain tissue mean probability map and the brain tissue initial probability map, specifically for the symmetric gray matter tissue mean probability map and the gray matter tissue initial probability map.
In an embodiment of the present invention, a tissue segmentation is performed on each of the preprocessed T2-weighted mr brain images and each of the T2-weighted mr flip brain images based on the initial probability map of the target brain tissue and the T2 standard template by using an SPM12 unified segmentation algorithm. Since the SPM12 unified segmentation algorithm unifies the spatial registration and the tissue segmentation, that is, step 2041 and step 2042 are simultaneously completed under the SPM12 unified segmentation algorithm.
FIG. 3 is another embodiment of the present invention, which is a method for constructing a brain template of a spontaneously hypertensive rat. As shown in fig. 3, the finally obtained brain template is a dispersion parameter standard template; the dispersion parameter standard template specifically comprises an FA standard template, an MD standard template and a b0 standard template. As shown in fig. 3, the method for constructing the spontaneous hypertensive rat brain template in this embodiment further includes the following steps:
and 301, performing binarization processing on the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map respectively to obtain a gray matter tissue mask, a white matter tissue mask and a cerebrospinal fluid tissue mask.
In the embodiment of the invention, the mask is a mask, and points on the probability map are subjected to binarization classification during binarization processing, namely each pixel point on the probability map is 1 (white) or 0 (black).
In an embodiment, when the gray matter tissue probability map, the white matter tissue probability map, and the cerebrospinal fluid tissue probability map are binarized, specifically, the threshold of the probability is set to 0.5, that is, the pixel points on the gray matter tissue probability map, the white matter tissue probability map, and the cerebrospinal fluid tissue probability map with the probability greater than 0.5 are set to 1 (white), and the pixel points with the probability less than 0.5 are set to 0 (black).
In the embodiment of the present invention, the diffusion tensor magnetic resonance image (DTI image) refers to an MRI image obtained by performing DTI scan. In one embodiment, is an MRI image obtained using an MS GRE EPI sequence line DTI scan.
In a specific embodiment, the preprocessing is performed on all diffusion tensor magnetic resonance images to obtain a plurality of diffusion parameter maps corresponding to each diffusion tensor magnetic resonance image, specifically, the preprocessing is performed on the diffusion tensor magnetic resonance images by using FSL software to extract b0 images, and eddy current correction and diffusion direction correction are performed to obtain an FA map and an MD map through calculation. Where FA is the anisotropy fraction and MD is the average diffusivity.
In one embodiment, the preprocessing of all the diffusion tensor magnetic resonance images further comprises voxel up-scaling all the diffusion tensor magnetic resonance images to a preset multiple. In a specific embodiment, the preset multiple is 10 times. The effect of the voxel amplification preprocessing is to make the size of the brain image of the spontaneously hypertensive rat adaptable to conventional human-developed image data processing software.
And 303, respectively turning each diffusion parameter map left and right to obtain a diffusion parameter turning map corresponding to each diffusion parameter map.
And step 304, registering each diffusion parameter map and the corresponding diffusion parameter inverse map to the T2 standard template respectively.
In the embodiment of the invention, in the magnetic resonance image of each spontaneous hypertension rat, the diffusion tensor magnetic resonance image and the T2 weighted magnetic resonance brain image are in one-to-one correspondence, namely, the same spontaneous hypertension rat is subjected to DTI scanning when T2WI scanning is carried out at the same week age.
In one embodiment, step 304 specifically includes the following sub-steps:
registering each diffusion tensor magnetic resonance image of each spontaneous hypertension rat to a T2 weighted magnetic resonance brain image of the spontaneous hypertension rat to obtain all primarily registered diffusion tensor magnetic resonance images;
respectively registering each diffusion tensor magnetic resonance flip image of each spontaneous hypertension rat to a T2 weighted magnetic resonance flip brain image of the spontaneous hypertension rat to obtain all primarily registered diffusion tensor magnetic resonance flip images;
acquiring a transformation relation between each preprocessed T2 weighted magnetic resonance brain image and each T2 weighted magnetic resonance flip brain image registered on a T2 standard template;
transforming the primarily registered diffusion tensor magnetic resonance image by using each primarily registered diffusion tensor magnetic resonance image and the corresponding transformation relation to obtain registered diffusion parameter images corresponding to all the diffusion parameter images;
and transforming the primarily registered diffusion tensor magnetic resonance flip image by using each primarily registered diffusion tensor magnetic resonance flip image and the corresponding transformation relation to obtain the registered diffusion parameter flip images corresponding to all the diffusion parameter maps.
In one embodiment, the transformation relationship between each preprocessed T2-weighted mr brain image and each T2-weighted mr flip brain image registered to the T2 standard template is obtained by performing transformation separately or by recording the registration segmentation process of step 2041 and step 2042.
And 305, carrying out image averaging on the registered diffusion parameter graphs of the same kind and the corresponding registered diffusion parameter reversal graphs, and carrying out image reversal and averaging on the averaged images to obtain the diffusion parameter initial templates corresponding to each kind of diffusion parameter graphs.
And step 306, obtaining the dispersion parameter template corresponding to each kind of dispersion parameter map by repeatedly iterating through the methods of spatial registration, image averaging, averaging image inversion re-averaging and residual error calculation by using the same kind of dispersion parameter maps, the corresponding dispersion parameter inverse maps and the corresponding dispersion parameter initial templates.
In the embodiment of the present invention, the obtaining of the dispersion parameter template corresponding to each dispersion parameter map by repeatedly iterating the same kind of dispersion parameter maps, the corresponding dispersion parameter inverse maps and the corresponding dispersion parameter initial templates through methods of spatial registration, image averaging, average image inverse re-averaging and residual error calculation includes:
step 3061, registering the same kind of diffusion parameter images and the corresponding diffusion parameter turning images on the corresponding diffusion parameter initial templates respectively, and carrying out image averaging on all registered images to obtain a third initial average image corresponding to each kind of diffusion parameter images;
step 3062, the third initial average image corresponding to each diffusion parameter map is flipped left and right to obtain a flipped image of the third initial average image corresponding to each diffusion parameter map, and the flipped images of the third initial average image corresponding to each diffusion parameter map and the third initial average image corresponding to each diffusion parameter map are subjected to image averaging to obtain a symmetrical third initial average image corresponding to each diffusion parameter map.
Step 3063, calculating the residual error between the symmetrical third initial average image corresponding to each diffusion parameter map and the corresponding diffusion parameter initial template, and if the residual error is smaller than a fourth preset value, accepting the symmetrical third initial average image as the diffusion parameter template corresponding to the diffusion parameter map.
And if the residual error is larger than or equal to a fourth preset value, taking the symmetrical third initial average image as a new diffusion parameter initial template, repeating the step 3061, the step 3062 and the step 3063 until the residual error is smaller than the fourth preset value, and obtaining the diffusion parameter template corresponding to each diffusion parameter map.
And 307, stripping non-brain tissues from the dispersion parameter template corresponding to each dispersion parameter map by using the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask to obtain a dispersion parameter standard template corresponding to each dispersion parameter map.
In the embodiment of the invention, the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask are used for stripping off the non-brain tissue from the diffusion parameter template. Specifically, white parts of the three masks of the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask in the embodiment of the present invention correspond to a brain tissue part, the three masks are covered and simultaneously covered on the diffusion parameter template to be processed, and a part of the diffusion parameter template to be processed, where a pixel on the mask is 1, and the part of the diffusion parameter template to be processed and the part of the mask to be processed, can be calculated. The mask is adopted for tissue segmentation, so that the non-brain tissue can be stripped manually, and the time cost is saved.
FIG. 4 is a schematic flow chart of another method for constructing a spontaneous hypertensive rat brain template according to an embodiment of the present invention. As shown in fig. 4, the brain template finally obtained is a functional magnetic resonance image template; further, the functional magnetic resonance image template specifically comprises an EPI standard template. As shown in fig. 4, the method for constructing the spontaneous hypertensive rat brain template in this embodiment further includes the following steps:
In the embodiment of the invention, the mask is a mask, and points on the probability map are subjected to binarization classification during binarization processing, namely each pixel point on the probability map is 1 (white) or 0 (black).
In an embodiment, when the gray matter tissue probability map, the white matter tissue probability map, and the cerebrospinal fluid tissue probability map are binarized, specifically, the threshold of the probability is set to 0.5, that is, the pixel points on the gray matter tissue probability map, the white matter tissue probability map, and the cerebrospinal fluid tissue probability map with the probability greater than 0.5 are set to 1 (white), and the pixel points with the probability less than 0.5 are set to 0 (black).
Step 402, preprocessing the functional magnetic resonance image of each spontaneous hypertensive rat to obtain a first functional magnetic resonance image.
In the embodiment of the present invention, the functional magnetic resonance image refers to an image obtained by performing fMRI scanning. Specifically, the EPI images were obtained by fMRI scanning using the SE GRE EPI sequence. In an experiment (Session) of a few minutes, several hundreds to several thousands of images are generated at an extremely fast acquisition rate of an EPI sequence, and a brain volume of several tens of different times becomes a Time-series (Time-series Image) of EPI images.
In an embodiment of the present invention, the functional magnetic resonance image of each spontaneously hypertensive rat comprises 200 EPI images corresponding to 200 time points. Before the functional magnetic resonance image of each spontaneous hypertension rat is preprocessed, the method also comprises the step of rejecting the EPI images corresponding to the first 10 time points in the EPI images, so that the processing can exclude the rat states and unstable images of scanning equipment at the first 10 time points, and therefore the error of the images is reduced.
In a specific embodiment, the preprocessing of the functional magnetic resonance image of each spontaneously hypertensive rat specifically comprises: and performing time-layer correction and head movement correction on all the EPI images of each spontaneous hypertension rat, and then performing image averaging on the corrected EPI images to obtain the first functional magnetic resonance image. In some embodiments, the preprocessing further comprises voxel-wise amplifying the functional magnetic resonance image of each spontaneously hypertensive rat to a preset magnification before the temporal slice correction and the cranial movement correction. In a specific embodiment, the preset multiple is 10 times. The effect of the voxel amplification preprocessing is to make the size of the brain image of the spontaneously hypertensive rat adaptable to conventional human-developed image data processing software.
And step 403, flipping all the first functional magnetic resonance images left and right to obtain first functional magnetic resonance flipped images.
In the embodiment of the invention, the first functional magnetic resonance image and the T2 weighted magnetic resonance brain image of each spontaneous hypertensive rat are in one-to-one correspondence, namely, the same spontaneous hypertensive rat is also subjected to fMRI scanning when T2WI scanning is carried out at the same week age.
In one embodiment, step 404 specifically includes the following sub-steps:
registering the first functional magnetic resonance image of each spontaneous hypertensive rat on the T2 weighted magnetic resonance brain image of the spontaneous hypertensive rat to obtain all primary registered first functional magnetic resonance images;
registering the first functional magnetic resonance flip image of each spontaneous hypertensive rat on a T2 weighted magnetic resonance flip brain image of the spontaneous hypertensive rat to obtain all primarily registered first functional magnetic resonance flip images;
acquiring a transformation relation between each preprocessed T2 weighted magnetic resonance brain image and each T2 weighted magnetic resonance flip brain image registered on a T2 standard template;
transforming the primarily registered first functional magnetic resonance image by using each primarily registered first functional magnetic resonance image and the corresponding transformation relation to obtain all standardized first functional magnetic resonance images; and
and transforming the primarily registered first functional magnetic resonance flip image by utilizing each primarily registered first functional magnetic resonance flip image and the corresponding transformation relation to obtain all standardized first functional magnetic resonance flip images.
In one embodiment, the transformation relationship between each preprocessed T2-weighted mr brain image and each T2-weighted mr flip brain image registered to the T2 standard template is obtained by performing transformation separately or by recording the registration segmentation process of step 2041 and step 2042.
And 406, repeatedly iterating by using all the first functional magnetic resonance images, all the first functional magnetic resonance inverted images and the functional magnetic resonance image initial template through methods of spatial registration, image averaging, image inversion re-averaging and residual calculation to obtain a functional magnetic resonance image template.
In the embodiment of the invention, the functional magnetic resonance image template is obtained by repeatedly iterating by using all the first functional magnetic resonance images, all the first functional magnetic resonance overturn images and the functional magnetic resonance image initial template through methods of spatial registration, image averaging, average image overturn re-averaging and residual error calculation; the method comprises the following steps:
step 4061, registering all the first functional magnetic resonance images and all the first functional magnetic resonance flip images to the functional magnetic resonance image initial template, and performing image averaging on all the registered images to obtain a fourth initial average image;
step 4062, left-right flipping the fourth initial average image to obtain a flipped image of the fourth initial average image, and performing image averaging on the flipped images of the fourth initial average image and the fourth initial average image to obtain a symmetric fourth initial average image.
Step 4063, respectively calculating a residual between the symmetric fourth initial average image and the functional magnetic resonance image initial template, and if the residual is smaller than a fifth predetermined value, accepting the symmetric fourth initial average image as the functional magnetic resonance image template.
And if the residual error is larger than or equal to a fifth preset value, taking the symmetrical fourth initial average image as a new functional magnetic resonance image initial template, and repeating the steps 4061, 4062 and 4063 until the residual error is smaller than the fifth preset value to obtain the functional magnetic resonance image template.
And 407, stripping non-brain tissues of the functional magnetic resonance image template by using the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask to obtain a functional magnetic resonance image standard template.
In the embodiment of the invention, the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask are used for stripping off the non-brain tissue of the functional magnetic resonance image template. Specifically, white parts of three masks, namely a gray matter tissue mask, a white matter tissue mask and a cerebrospinal fluid tissue mask in the embodiment of the present invention correspond to a brain tissue part, and the three masks are covered and simultaneously covered on a functional magnetic resonance image template to be processed, so that a part of the functional magnetic resonance image template to be processed, where a pixel on the mask is 1, and a part of the functional magnetic resonance image template to be processed, can be calculated. The mask is adopted for tissue segmentation, so that the non-brain tissue can be stripped manually, and the time cost is saved.
The first, second, third, fourth and fifth predetermined values in embodiments of the present invention may be 5%, generally considering that when the residual is less than 5%, the images are already accurately registered.
In one embodiment, the scanning process of the magnetic resonance brain images of multiple spontaneous hypertensive rats is performed continuously, that is, T2WI scan, DTI scan and fMRI scan are performed continuously on the same spontaneous hypertensive rat, so that the T2 weighted magnetic resonance brain image, the diffusion tensor magnetic resonance image and the functional magnetic resonance image of the same spontaneous hypertensive rat are measured in the same state of the same rat, and therefore, the registration accuracy is better.
Fig. 5 is a schematic flow chart of a method for constructing a map set of spontaneously hypertensive rats according to an embodiment of the present invention, and as shown in fig. 5, the method for constructing a map set of spontaneously hypertensive rats according to an embodiment of the present invention includes the following steps:
In the present example, the construction of a map of spontaneously hypertensive rats using a Tohoku T2 template and a Tohoku map (https:// scalabletalinalas. incf. org/rat/VSNetal11) was carried out using Wistar rats, which are also naturally derived from Wistar rats, and the establishment of a map of spontaneously hypertensive rats using a Tohoku T2 template and a Tohoku map allows better correspondence of the map to spontaneously hypertensive rats while saving time and cost due to the homology between the two.
In the embodiment of the present invention, the obtaining of the first transformation relationship of the Tohoku T2 template registered to the T2 standard template obtained by the above construction method may specifically be performed by registering a Tohoku T2 template to the T2 standard template in the implementation of the present invention, and recording the transformation relationship of the registration process as the first transformation relationship.
In the embodiment of the invention, the Tohoku map set is transformed by utilizing the first transformation relation, and then the right cortical structure in the transformed Tohoku map set is taken as the target right cortical structure, so that the method is simple and the time cost is saved.
In one embodiment, the target right cortical structure specifically includes a plurality of right cortical brain regions, and each right cortical brain region corresponds to a tag. In the Tohoku map set, the number of right cortical brain regions is 48, and the number of target right cortical brain regions is also 48.
In the embodiment of the invention, a T2 standard template, a gray matter tissue probability map, a white matter tissue probability map, a cerebrospinal fluid tissue probability map and a dispersion parameter standard template are referred when a target right-side subcortical structure is drawn, namely different brain templates need to be referred when different parts of the target right-side subcortical structure are drawn, and specifically, the part of the subcortical structure is drawn by taking the template as a main reference according to which brain template the part of the target right-side subcortical structure is most clear.
In one embodiment, the subcortical structures are rendered at the coronal level using the ITK-SNAP tool with contrast differences of images of different brain templates and tissue probability maps of different brain tissues, followed by repeated layer-by-layer modifications at the axial and sagittal levels.
In one embodiment, the target right sub-cortical structure comprises a plurality of first right sub-cortical brain regions and a plurality of second right sub-cortical brain regions, wherein each first right sub-cortical brain region is a complete brain region and each second right sub-cortical brain region is a half brain region. In one embodiment, the number of first right subcortical brain regions is 24 and the number of second right subcortical brain regions is 19.
And step 504, performing image calculation on the target right cortical structure to obtain a target left cortical structure symmetrical to the target right cortical structure.
In the embodiment of the invention, the target left-side cortical structure symmetrical to the target right-side cortical structure is obtained by performing image calculation on the target right-side cortical structure, and the target left-side sub-cortical structure symmetrical to the target right-side sub-cortical structure is obtained by performing image calculation on the target right-side sub-cortical structure; the spontaneous hypertension rat bilateral symmetry map set formed by the target right-side cortical structure, the target left-side cortical structure, the target right-side sub-cortical structure and the target left-side sub-cortical structure can be better applied to the research of other differences of the brain side, for example, the brain left-side and right-side differences in the brain aging process can be researched.
In one embodiment, the target right cortical structure comprises a plurality of right cortical brain regions, and the target left cortical structure comprises a plurality of left cortical brain regions, wherein each right cortical brain region corresponds to one left cortical brain region in a mirror image, and each right cortical brain region and each left cortical brain region correspond to one label; the target right subcortical structure comprises a plurality of first right subcortical brain regions and a plurality of second right subcortical brain regions, and the target left subcortical structure comprises a plurality of first left subcortical brain regions and a plurality of second left subcortical brain regions; each first right subcortical brain region is a complete brain region and corresponds to a first left subcortical brain region in a mirror image manner; each second right subcortical brain region is a half brain region and corresponds to a second left subcortical brain region in a mirror image manner to form a complete brain region; each first right-side subcortical brain region and each first left-side subcortical brain region respectively correspond to one label, and each second right-side subcortical brain region and the corresponding second left-side subcortical brain region jointly correspond to one label; each of which is different from the others.
The method in the embodiment of the invention has the following advantages: (1) the brain template is manufactured by using the in-vivo MRI technology, so that the brain structure of the rat is reflected more truly. And the long span of the longitudinal scan makes the present template suitable for SHR in all stages from early adulthood to elderly. (2) By utilizing various magnetic resonance imaging means, richer information is provided from various contrasts of structure, diffusion characteristics and brain functions, and the multi-modal templates are all in the same spatial coordinate. (3) Although the mouse brain tissue has lateralization characteristics, a symmetric template is still needed for specially researching the brain difference, otherwise, the side difference is possibly caused by the aliasing of an asymmetric brain template, so that the research result is unreliable; the brain template and the map set in the embodiment of the invention are symmetrical, so that the study of different brain differences is facilitated. (4) The embodiment of the invention provides a Tissue Probability Map (TPM) of gray matter, white matter and cerebrospinal fluid, which provides a basis for the segmentation of brain tissue. The TPM can be used for directly utilizing a unified segmentation algorithm of SPM software to realize the segmentation of individual brain tissues, and further realize the morphological analysis (VBM) (5) based on voxels, a full brain map set of 163 brain areas is generated in one specific embodiment of the invention, the accurate positioning and brain area extraction of SHR brain tissues can be realized, and a basis is provided for the construction of a structure or function network map in a full brain range.
In one embodiment, as shown in fig. 6, there is provided an electronic device including: a data receiving unit 601, a preprocessing unit 602, a first image flipping unit 603, a first reference template obtaining unit 604, a first calculating unit 605, a second image flipping unit 606, and a second calculating unit 607; wherein:
a data receiving unit 601 for receiving magnetic resonance brain images of a plurality of spontaneously hypertensive rats, each of the magnetic resonance brain images of spontaneously hypertensive rats comprising a T2 weighted magnetic resonance brain image;
a preprocessing unit 602 for preprocessing the T2 weighted magnetic resonance brain image of each spontaneously hypertensive rat, said preprocessing including the ablation of non-brain tissue;
the first image flipping unit 603 is configured to flip left and right the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertensive rat to obtain a corresponding T2 weighted magnetic resonance flipped brain image;
a first reference template acquisition unit 604; the method comprises the steps of obtaining a first reference template selection instruction, and taking a preprocessed T2 weighted magnetic resonance brain image of a specified spontaneous hypertensive rat carried by the first reference template selection instruction as a first reference template;
a first calculating unit 605, configured to obtain a first average image by repeatedly iterating through methods of spatial registration, image averaging, and residual calculation, using all preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template;
a second image flipping unit 606, configured to flip the first average image left and right to obtain a first average flipped image, and perform image averaging on the first average image and the first average flipped image to obtain a second reference template; and
a second calculation unit 607; and repeatedly iterating the method for spatial registration, image averaging, mean image inversion re-averaging and residual calculation by utilizing all the preprocessed T2 weighted magnetic resonance brain images, all the preprocessed T2 weighted magnetic resonance inverted brain images and the second reference template to obtain the T2 standard template.
In another embodiment of the present invention, as shown in fig. 7, there is provided another electronic device including: a transformation relation obtaining unit 701, a target right cortical structure obtaining unit 702, a target right sub-cortical structure obtaining unit 703, a target left cortical structure obtaining unit 704 and a target left sub-cortical structure obtaining unit 705; wherein:
a transformation relation obtaining unit 701, configured to obtain a first transformation relation between the Tohoku T2 template and the T2 standard template obtained by the above-described construction method;
a target right cortical structure obtaining unit 702, configured to transform the Tohoku map set according to the first transformation relation, so as to obtain a target right cortical structure;
a target right-side subcortical structure obtaining unit 703, configured to, on the basis of the target right-side subcortical structure, respectively refer to the T2 standard template obtained by the above-described construction method, the gray matter tissue probability map, the white matter tissue probability map, and the cerebrospinal fluid tissue probability map obtained by the above-described construction method, and the dispersion parameter standard template obtained by the above-described construction method, draw the target right-side subcortical structure at the coronal level, and correct at the axial level and the sagittal level;
a target left cortical structure obtaining unit 704, configured to perform image calculation on the target right cortical structure, so as to obtain a target left cortical structure symmetric to the target right cortical structure; and
a target left-side subcortical structure acquisition unit 705 configured to perform image calculation on the target right-side subcortical structure to obtain a target left-side subcortical structure symmetric to the target right-side subcortical structure; wherein the target right-side cortical structure, target left-side cortical structure, target right-side sub-cortical structure, and target left-side sub-cortical structure comprise the map set of spontaneously hypertensive rats.
For the specific definition of an electronic device, reference may be made to the above definition of the method for constructing a spontaneous hypertensive rat brain template and the method for constructing a spontaneous hypertensive rat atlas, which are not described herein again. The units in the electronic device described above may be implemented wholly or partially by software, hardware, and a combination thereof. The units can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In the embodiment of the present invention, an electronic device is further provided, where the electronic device may be a computer device, the computer device may be a terminal, and an internal structure diagram of the electronic device may be as shown in fig. 8. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile 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 an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a phenotype-based gene prioritization method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, an electronic device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
receiving magnetic resonance brain images of a plurality of spontaneously hypertensive rats, the magnetic resonance brain images of each spontaneously hypertensive rat comprising a T2 weighted magnetic resonance brain image;
pre-processing the T2 weighted magnetic resonance brain image of each spontaneously hypertensive rat, said pre-processing including the ablation of non-brain tissue;
turning the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertension rat left and right to obtain a corresponding T2 weighted magnetic resonance turned brain image;
acquiring a first reference template selection instruction, and taking a preprocessed T2 weighted magnetic resonance brain image of a specified spontaneous hypertensive rat carried by the first reference template selection instruction as a first reference template;
repeatedly iterating by using all preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template through methods of spatial registration, image averaging and residual error calculation to obtain a first average image;
turning the first average image left and right to obtain a first average turned image, and carrying out image averaging on the first average image and the first average turned image to obtain a second reference template; and
and repeatedly iterating by using all the preprocessed T2 weighted magnetic resonance brain images, all the preprocessed T2 weighted magnetic resonance reversed brain images and the second reference template through methods of spatial registration, image averaging, mean image reversal re-averaging and residual error calculation to obtain a T2 standard template.
In another embodiment, an electronic device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring a first transformation relation of registering the Tohoku T2 template to the T2 standard template obtained by the construction method;
transforming the Tohoku map set according to the first transformation relation to obtain a target right cortex structure;
on the basis of the target right cortical structure, respectively referring to the T2 standard template obtained by the construction method, the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map obtained by the construction method, and the dispersion parameter standard template obtained by the construction method, drawing the target right subcortical structure at the coronal level and correcting at the axial level and the sagittal level;
performing image calculation on the target right cortex structure to obtain a target left cortex structure which is symmetrical to the target right cortex structure; and
performing image calculation on the target right-side subcortical structure to obtain a target left-side subcortical structure which is symmetrical to the target right-side subcortical structure;
wherein the target right-side cortical structure, target left-side cortical structure, target right-side sub-cortical structure, and target left-side sub-cortical structure comprise the map set of spontaneously hypertensive rats.
The electronic device in this embodiment may specifically be a computer device.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
receiving magnetic resonance brain images of a plurality of spontaneously hypertensive rats, the magnetic resonance brain images of each spontaneously hypertensive rat comprising a T2 weighted magnetic resonance brain image;
pre-processing the T2 weighted magnetic resonance brain image of each spontaneously hypertensive rat, said pre-processing including the ablation of non-brain tissue;
turning the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertension rat left and right to obtain a corresponding T2 weighted magnetic resonance turned brain image;
acquiring a first reference template selection instruction, and taking a preprocessed T2 weighted magnetic resonance brain image of a specified spontaneous hypertensive rat carried by the first reference template selection instruction as a first reference template;
repeatedly iterating by using all preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template through methods of spatial registration, image averaging and residual error calculation to obtain a first average image;
turning the first average image left and right to obtain a first average turned image, and carrying out image averaging on the first average image and the first average turned image to obtain a second reference template;
and repeatedly iterating by using all the preprocessed T2 weighted magnetic resonance brain images, all the preprocessed T2 weighted magnetic resonance reversed brain images and the second reference template through methods of spatial registration, image averaging, mean image reversal re-averaging and residual error calculation to obtain a T2 standard template.
In another embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when executed by a processor, performs the steps of:
acquiring a first transformation relation of registering the Tohoku T2 template to the T2 standard template obtained by the construction method;
transforming the Tohoku map set according to the first transformation relation to obtain a target right cortex structure;
on the basis of the target right cortical structure, respectively referring to the T2 standard template obtained by the construction method, the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map obtained by the construction method, and the dispersion parameter standard template obtained by the construction method, drawing the target right subcortical structure at the coronal level and correcting at the axial level and the sagittal level;
performing image calculation on the target right cortex structure to obtain a target left cortex structure which is symmetrical to the target right cortex structure; and
performing image calculation on the target right-side subcortical structure to obtain a target left-side subcortical structure which is symmetrical to the target right-side subcortical structure;
wherein the target right-side cortical structure, target left-side cortical structure, target right-side sub-cortical structure, and target left-side sub-cortical structure comprise the map set of spontaneously hypertensive rats.
Examples of the experiments
First, experimental animal
T2WI, DTI and fMRI scans were performed at 3 time points (weeks 10, 24 and 52) for 8 SHR, respectively. The rat breeding environment temperature is 22-24 deg.C, relative humidity is 50-60%, and 12 hr day and night alternate circulation is realized. All rats were on a standard diet with free access to water. Blood pressure measurements were taken in all rats at 20 weeks of age. Systolic pressure, diastolic pressure, mean arterial pressure were measured 3 times and averaged. Rat body weight measurements were made weekly from 8 to 52 weeks.
Two, multi-modality MRI scan
Scans were performed with a 7.0T bruke small animal magnetic resonance scanner. Rats were anesthetized with 3% isoflurane induction and then injected intramuscularly with 0.015mg/kg dexmedetomidine on the back of the right thigh. The isoflurane is mixed with medical oxygen to maintain anesthesia on a rat abdominal bed. Isoflurane 0.6-1.2% maintains respiratory rate 50-60 times/min for T2WI and DTI scan, and isoflurane 0.2-0.8% maintains respiratory rate 70 times/min before fMRI scan. Blood oxygen was monitored in real time during the scan and the rat body temperature was maintained at 37 ℃ with water bath heating.
T2WI, DTI and fMRI were scanned sequentially throughout the brain in the coronal phase. Scan with RARE sequence line T2WI, scan parameters: TR 10700ms, TE 36ms, RARE 8, FOV 35 × 35mm2The matrix is 256 × 256, and the spatial resolution is 0.137 × 0.137mm2The number of layers is 90, the layer thickness is 0.3mm, and the average number of times is 4. Scan with MS SE EPI sequence line DTI scan, scan parameters: TR 9300ms, TE 30ms, δ 4ms, Δ 15ms, the number of directions of dispersion 30, b 05, b 1000s/mm2，FOV＝35×35mm2The resolution is 0.273 × 0.273mm, and the matrix is 128 × 1282The number of layers is 37 and the layer thickness is 0.8 mm. Using SE GRE EPI sequence line fMRI scan, scan parameters: TR 2000ms, TE 10ms, flip angle 90 DEG, bandwidth 250kHz, FOV 25X 20mm2The matrix is 80 × 64, and the spatial resolution is 0.312 × 0.312mm2The number of layers is 37, the layer thickness is 0.8mm, and the number of repetitions is 200. The total scan time was about 60 minutes.
Third, template construction
By using the method in the embodiment of the invention, a T2 standard template, a gray matter tissue probability map, a white matter tissue probability map, a cerebrospinal fluid tissue probability map, an FA standard template, an MD standard template, a b0 standard template and an EPI standard template are respectively constructed.
In fig. 9, columns a and B represent slices of the T2 standard template at the coronal, axial and sagittal positions, respectively, columns B and C represent slices of the FA standard template at the coronal, axial and sagittal positions, respectively, columns C and D represent slices of the MD standard template at the coronal, axial and sagittal positions, respectively, columns D and D represent slices of the B0 standard template at the coronal, axial and sagittal positions, respectively, and columns E represent slices of the EPI standard template at the coronal, axial and sagittal positions, respectively, from top to bottom.
In fig. 10, column a represents slices of the gray matter tissue probability map at the coronal, axial and sagittal positions from top to bottom, column B represents slices of the white matter tissue probability map at the coronal, axial and sagittal positions from top to bottom, column C represents slices of the cerebrospinal fluid tissue probability map at the coronal, axial and sagittal positions from top to bottom, and column D represents pseudo-color TPMs superimposed on the T2 standard template image, which are coronal, axial and sagittal positions from top to bottom.
Construction of map set
By using the method in the embodiment of the invention, a map set of spontaneous hypertensive rats is constructed, as shown in fig. 10. Wherein the number of the target right-side cortical brain regions is 48, the number of the first right-side cortical subconcephalic regions is 24, and the number of the second right-side cortical subconcephalic regions is 19. After image calculation, the final atlas includes 96 cortical brain regions, 67 subcortical brain regions, and 163 brain regions in total.
FIG. 11 is a map set of spontaneously hypertensive rats obtained in this experimental example, wherein two columns A and B represent slices of the map set from caudal to cephalic in coronal position, respectively, two columns C represent slices of the map set from axial position to median sagittal position, respectively, and two columns D represent the presentation of the map set from dorsal position to ventral position in a three-dimensional image, respectively.
Fifth, evaluation of template
The similarity coefficient (DICE), Hausdorff Distance (HD), of the individual space T2WI image to the template space was compared (10, 24, 52 weeks old) from gray matter, white matter, cerebrospinal fluid and whole brain levels, respectively. The results are shown in FIG. 12, where A represents the similarity coefficient (DICE) and B represents the Hausdorff Distance (HD), where GM represents gray matter, WM represents white matter, CSF represents cerebrospinal fluid and Brain represents whole Brain.
And calculating the volumes of gray matter, white matter, cerebrospinal fluid and whole brain of the individual space, and comparing the volume values of different brain tissues in the template space to obtain the volume variation Coefficient (CV), the Relative Volume Difference (RVD) and the Absolute Volume Difference (AVD) of the gray matter, the white matter, the cerebrospinal fluid and the whole brain at each age stage. The results are shown in FIG. 13, where A represents Coefficient of Variation (CV), B represents Relative Volume Difference (RVD), C represents Absolute Volume Difference (AVD), where GM represents gray matter, WM represents white matter, CSF represents cerebrospinal fluid, and Brain represents Brain.
The above evaluation index values for whole brain levels at 10, 24, and 52 weeks were: DICE 94.2 + -1.1%, 96.7 + -0.6%, 96.0 + -0.7%; HD 16.3 +/-1.1 mm, 9.8 +/-2.1 mm and 12.1 +/-2.8 mm; CV 3.11%, 3.27%, 2.63%; RVD 8.9 +/-2.8%, 3.4 +/-1.8% and 6.4 +/-2.8%; AVD 9.4 + -3.1%, 3.3 + -1.7%, 6.2 + -2.6%. The level of the 10-week-old SHR cerebrospinal fluid DICE is minimum and reaches 90.6 +/-0.9%; the level of HD was maximal at the level of the whole brain of 10-week-old SHR, 16.3. + -. 1.1 mm. The maximum CV of volume variation is 10 weeks at the cerebrospinal fluid level, which reaches 6.4%. We quantitatively evaluated and confirmed the accuracy of the template from gray matter, white matter, cerebrospinal fluid and whole brain levels by calculating the Dice coefficient, Hausdorff distance, coefficient of variation of mouse brain volume, absolute volume difference and relative volume difference.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by hardware instructions related to a program, which may be stored in a computer-readable storage medium, and the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by hardware that is instructed to implement by a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
While the invention has been described in detail with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention.
Claims (10)
1. A construction method of a spontaneous hypertensive rat brain template is characterized by comprising the following steps:
receiving magnetic resonance brain images of a plurality of spontaneously hypertensive rats, the magnetic resonance brain images of each spontaneously hypertensive rat comprising a T2 weighted magnetic resonance brain image;
pre-processing the T2 weighted magnetic resonance brain image of each spontaneously hypertensive rat, said pre-processing including the ablation of non-brain tissue;
turning the preprocessed T2 weighted magnetic resonance brain image of each spontaneous hypertension rat left and right to obtain a corresponding T2 weighted magnetic resonance turned brain image;
receiving a first reference template selection instruction, and selecting a preprocessed T2 weighted magnetic resonance brain image indicated by the first reference template selection instruction as a first reference template;
repeatedly iterating by using all preprocessed T2 weighted magnetic resonance brain images except the first reference template and the first reference template through methods of spatial registration, image averaging and residual error calculation to obtain a first average image;
turning the first average image left and right to obtain a first average turned image, and carrying out image averaging on the first average image and the first average turned image to obtain a second reference template; and
and repeatedly iterating by using all the preprocessed T2 weighted magnetic resonance brain images, all the preprocessed T2 weighted magnetic resonance reversed brain images and the second reference template through methods of spatial registration, image averaging, mean image reversal re-averaging and residual error calculation to obtain a T2 standard template.
2. The building method according to claim 1, further comprising:
carrying out target brain tissue segmentation on the T2 standard template to obtain a first target brain tissue probability map, wherein the target brain tissue comprises: gray matter, white matter and cerebrospinal fluid;
turning the first target brain tissue probability map left and right to obtain a corresponding first target brain tissue probability turning map;
carrying out image averaging on the first target brain tissue probability map and the first target brain tissue probability inversion map to obtain a target brain tissue initial probability map; and
and (3) utilizing the initial probability map of the target brain tissue and the T2 standard template to repeatedly iterate each preprocessed T2 weighted magnetic resonance brain image and each preprocessed T2 weighted magnetic resonance reversed brain image through methods of space registration, tissue segmentation, image averaging, mean image reversal re-averaging and residual error calculation to obtain the probability map of the target brain tissue.
3. The construction method according to claim 2, wherein the magnetic resonance brain image of each spontaneously hypertensive rat comprises a diffusion tensor magnetic resonance image;
the construction method further comprises the following steps:
respectively carrying out binarization processing on the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map to obtain a gray matter tissue mask, a white matter tissue mask and a cerebrospinal fluid tissue mask;
preprocessing all the diffusion tensor magnetic resonance images to obtain a plurality of diffusion parameter graphs corresponding to each diffusion tensor magnetic resonance image;
turning each diffusion parameter graph left and right respectively to obtain a diffusion parameter turning graph corresponding to each diffusion parameter graph respectively;
registering each diffusion parameter map and the corresponding diffusion parameter flip map to the T2 standard template respectively;
carrying out image averaging, average image overturning and re-averaging on the registered diffusion parameter graphs of the same kind and the corresponding registered diffusion parameter overturning graphs to obtain diffusion parameter initial templates corresponding to each kind of diffusion parameter graphs;
obtaining a dispersion parameter template corresponding to each kind of dispersion parameter image by repeated iteration through methods of spatial registration, image averaging, averaging after image inversion and residual calculation by using the same kind of dispersion parameter images, corresponding dispersion parameter inversion images and corresponding dispersion parameter initial templates; and
and stripping non-brain tissue from the dispersion parameter template corresponding to each dispersion parameter map by using the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask to obtain the dispersion parameter standard template corresponding to each dispersion parameter map.
4. The construction method according to claim 3, wherein the dispersion parameter map comprises an FA map, an MD map and a b0 map, and the standard templates corresponding to the FA map, the MD map and the b0 map are an FA standard template, an MD standard template and a b0 standard template, respectively.
5. The construction method according to claim 2, wherein the magnetic resonance brain image of each spontaneously hypertensive rat comprises a functional magnetic resonance image;
the construction method further comprises the following steps:
respectively carrying out binarization processing on the gray matter tissue probability map, the white matter tissue probability map and the cerebrospinal fluid tissue probability map to obtain a gray matter tissue mask, a white matter tissue mask and a cerebrospinal fluid tissue mask;
preprocessing the functional magnetic resonance image of each spontaneous hypertension rat to obtain a first functional magnetic resonance image;
turning all the first functional magnetic resonance images left and right to obtain first functional magnetic resonance turned images;
registering all the first functional magnetic resonance images and all the first functional magnetic resonance flip images to the T2 standard template to obtain standardized first functional magnetic resonance images and standardized first functional magnetic resonance flip images;
carrying out image averaging on all the standardized first functional magnetic resonance images and the standardized first functional magnetic resonance overturning images, overturning and averaging the average images, and obtaining a functional magnetic resonance image initial template;
repeatedly iterating all the first functional magnetic resonance images, all the first functional magnetic resonance overturning images and the functional magnetic resonance image initial template through methods of space registration, image averaging, averaging image overturning and averaging again and residual error calculation to obtain a functional magnetic resonance image template; and
and stripping non-brain tissues of the functional magnetic resonance image template by using the gray matter tissue mask, the white matter tissue mask and the cerebrospinal fluid tissue mask to obtain a functional magnetic resonance image standard template.
6. The construction method according to claim 5, characterized in that the functional magnetic resonance image comprises an EPI image and the functional magnetic resonance image standard template comprises an EPI standard template.
7. A method for constructing a map set of spontaneously hypertensive rats, comprising the following steps:
acquiring a first transformation relation of a Tohoku T2 template registered to a T2 standard template obtained by the construction method of claim 1;
transforming the Tohoku map set according to the first transformation relation to obtain a target right cortex structure;
on the basis of the target right cortical structure, respectively referring to a T2 standard template obtained by the construction method of claim 1, a gray matter tissue probability map, a white matter tissue probability map and a cerebrospinal fluid tissue probability map obtained by the construction method of claim 2, and a dispersion parameter standard template obtained by the construction method of claim 3 or 4, drawing the target right subcortical structure at a coronal level and correcting at an axial level and a sagittal level;
performing image calculation on the target right cortex structure to obtain a target left cortex structure which is symmetrical to the target right cortex structure; and
performing image calculation on the target right-side subcortical structure to obtain a target left-side subcortical structure which is symmetrical to the target right-side subcortical structure;
wherein the target right-side cortical structure, target left-side cortical structure, target right-side sub-cortical structure, and target left-side sub-cortical structure comprise the map set of spontaneously hypertensive rats.
8. The construction method according to claim 7, wherein the target right cortical structure comprises a plurality of right cortical brain regions, and the target left cortical structure comprises a plurality of left cortical brain regions, wherein each right cortical brain region corresponds to one left cortical brain region in a mirror image manner, and each right cortical brain region and each left cortical brain region correspond to one label respectively;
the target right sub-cortical structure comprises a plurality of first right sub-cortical sub-brain regions and a plurality of second right sub-cortical sub-brain regions, and the target left sub-cortical sub-structure comprises a plurality of first left sub-cortical sub-brain regions and a plurality of second left sub-cortical sub-brain regions; each first right subcortical brain region is a complete brain region and corresponds to a first left subcortical brain region in a mirror image manner; each second right subcortical brain region is a half brain region and corresponds to a second left subcortical brain region in a mirror image manner to form a complete brain region; each first right-side subcortical brain region and each first left-side subcortical brain region respectively correspond to one label, and each second right-side subcortical brain region and the corresponding second left-side subcortical brain region jointly correspond to one label; each of which is different from the others.
9. An electronic device, comprising:
one or more processors;
a memory;
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the build method of any of claims 1-8.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the building method of any one of claims 1 to 8.
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| 磁共振弥散张量成像在中枢神经系统中的应用;杨迎迎等;《中国介入影像与治疗学》;20130310;第10卷(第03期);第183-186页 * |
| 老化及高血压对大脑静息态低频振幅与空间认知能力的影响;张勇智;《中国优秀硕士学位论文全文数据库_医药卫生科技辑》;20210215(第02期);E060-233 * |
| 老化及高血压对脑组织微观结构影响的扩散峰度成像研究;刘上聘;《中国优秀硕士学位论文全文数据库_医药卫生科技辑》;20210215(第02期);E060-234 * |
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