Method and apparatus of fiber tracking, and non-transitory computer-readable medium thereof
First Claim
1. A method of fiber tracking, comprising:
- receiving a first diffusion weighted image of a subject'"'"'s brain;
obtaining N tracking parameters from a first relation matrix stored in a storage unit according to first N of all similarities of the first relation matrix, wherein N is a positive integer greater than or equal to 8;
performing a fiber tracking process on the first diffusion weighted image according to each of the N tracking parameters, to obtain a plurality of first tracking images;
obtaining two first regions of interest according to a predetermined fasciculus;
extracting a plurality of nerve fibers between the two first regions of interest in each of the plurality of first tracking images;
according to the plurality of nerve fibers extracted from the plurality of first tracking images, obtaining nerve fasciculus probabilities of overlapped voxels based on an overlapping equation, wherein the overlapping equation is Tj=norm(Σ
i=1nwi×
(tj)i), and Tj is a nerve fasciculus probability of the j-th overlapped voxel, wi is a similarity corresponding to the i-th predetermined tracking parameter, (tj)i is a quantity of the nerve fibers of the j-th image voxel of the first tracking image obtained according to the i-th predetermined tracking parameter, and the j-th overlapped voxel corresponds in position to the j-th image voxel of each of the plurality of first tracking images, and i and j are positive integers;
among the overlapped voxels, selecting the overlapped voxels having the top one to ten percent of nerve fasciculus probabilities to establish a nerve fasciculus skeleton; and
comparing structural similarities between the nerve fasciculus skeleton and the extracted nerve fibers in each of the plurality of first tracking images, to obtain a plurality of evaluation values, and then obtaining a specific fasciculus according to the nerve fibers having the top thirty-three to sixty-six percent of the evaluation values.
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Accused Products
Abstract
The present disclosure illustrates a method and an apparatus of fiber tracking, and non-transitory computer-readable medium thereof. In an embodiment, a fiber tracking process is performed on a diffusion magnetic resonance image of a subject'"'"'s brain based on validated and better tracking parameters, so as to obtain first tracking images, nerve fibers between two first regions of interest in each of the first tracking images are extracted, a nerve fasciculus skeleton is established based on an overlapping process performed on the plurality of nerve fibers extracted from the first tracking images, and the nerve fibers more similar to the structure of the nerve fasciculus skeleton are selected to obtain a specific fasciculus of the subject. Thus, the technical solution of the present disclosure can be used to improve the sensitivity of fiber tracking and be useful for improvement of preoperative assessment and surgical navigation.
4 Citations
9 Claims
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1. A method of fiber tracking, comprising:
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receiving a first diffusion weighted image of a subject'"'"'s brain; obtaining N tracking parameters from a first relation matrix stored in a storage unit according to first N of all similarities of the first relation matrix, wherein N is a positive integer greater than or equal to 8; performing a fiber tracking process on the first diffusion weighted image according to each of the N tracking parameters, to obtain a plurality of first tracking images; obtaining two first regions of interest according to a predetermined fasciculus; extracting a plurality of nerve fibers between the two first regions of interest in each of the plurality of first tracking images; according to the plurality of nerve fibers extracted from the plurality of first tracking images, obtaining nerve fasciculus probabilities of overlapped voxels based on an overlapping equation, wherein the overlapping equation is Tj=norm(Σ
i=1nwi×
(tj)i), and Tj is a nerve fasciculus probability of the j-th overlapped voxel, wi is a similarity corresponding to the i-th predetermined tracking parameter, (tj)i is a quantity of the nerve fibers of the j-th image voxel of the first tracking image obtained according to the i-th predetermined tracking parameter, and the j-th overlapped voxel corresponds in position to the j-th image voxel of each of the plurality of first tracking images, and i and j are positive integers;among the overlapped voxels, selecting the overlapped voxels having the top one to ten percent of nerve fasciculus probabilities to establish a nerve fasciculus skeleton; and comparing structural similarities between the nerve fasciculus skeleton and the extracted nerve fibers in each of the plurality of first tracking images, to obtain a plurality of evaluation values, and then obtaining a specific fasciculus according to the nerve fibers having the top thirty-three to sixty-six percent of the evaluation values. - View Dependent Claims (2, 3, 4)
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5. A non-transitory computer-readable medium for fiber tracking, configured to store operating instructions which are executed by at least one processor to execute following operations:
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receiving a first diffusion weighted image of a subject'"'"'s brain; obtaining N tracking parameters from a first relation matrix stored in a storage unit according to first N of all similarities of the first relation matrix, wherein N is a positive integer greater than or equal to 8; performing a fiber tracking process on the first diffusion weighted image according to each of the N tracking parameters, to obtain a plurality of first tracking images; obtaining two first regions of interest according to a predetermined fasciculus; extracting a plurality of nerve fibers between the two first regions of interest in each of the plurality of first tracking images; according to the plurality of nerve fibers extracted from the plurality of first tracking images, obtaining nerve fasciculus probabilities of overlapped voxels based on an overlapping equation, wherein the overlapping equation is Tj=norm(Σ
i=1nwi×
(tj)i), and Tj is a nerve fasciculus probability of the j-th overlapped voxel, wi is a similarity corresponding to the i-th predetermined tracking parameter, (tj)i is a quantity of the nerve fibers of the j-th image voxel of the first tracking image obtained according to the i-th predetermined tracking parameter, and the j-th overlapped voxel corresponds in position to the j-th image voxel of each of the plurality of first tracking images, and i and j are positive integers;among the overlapped voxels, selecting the overlapped voxels having the top one to ten percent of nerve fasciculus probabilities to establish a nerve fasciculus skeleton; and comparing structural similarities between the nerve fasciculus skeleton and the extracted nerve fibers in each of the plurality of first tracking images, to obtain a plurality of evaluation values, and then obtaining a specific fasciculus according to the nerve fibers having the top thirty-three to sixty-six percent of the evaluation values. - View Dependent Claims (6, 7, 8)
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9. An apparatus of fiber tracking, comprising:
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at least one processor; a storage unit; and at least one program stored in the storage unit and configured to be executed by the at least one processor, and at least one program comprises instructions for operations of; receiving a first diffusion weighted image of a subject'"'"'s brain; obtaining N tracking parameters from a first relation matrix stored in a storage unit according to first N of all similarities of the first relation matrix, wherein N is a positive integer greater than or equal to 8; performing a fiber tracking process on the first diffusion weighted image according to each of the N tracking parameters, to obtain a plurality of first tracking images; obtaining two first regions of interest according to a predetermined fasciculus; extracting a plurality of nerve fibers between the two first regions of interest in each of the plurality of first tracking images; according to the plurality of nerve fibers extracted from the plurality of first tracking images, obtaining nerve fasciculus probabilities of overlapped voxels based on an overlapping equation, wherein the overlapping equation is Tj=norm(Σ
i=1nwi×
(tj)i), and Tj is a nerve fasciculus probability of the j-th overlapped voxel, wi is a similarity corresponding to the i-th predetermined tracking parameter, (tj)i is a quantity of the nerve fibers of the j-th image voxel of the first tracking image obtained according to the i-th predetermined tracking parameter, and the j-th overlapped voxel corresponds in position to the j-th image voxel of each of the plurality of first tracking images, and i and j are positive integers;among the overlapped voxels, selecting the overlapped voxels having the top one to ten percent of nerve fasciculus probabilities to establish a nerve fasciculus skeleton; and comparing structural similarities between the nerve fasciculus skeleton and the extracted nerve fibers in each of the plurality of first tracking images, to obtain a plurality of evaluation values, and then obtaining a specific fasciculus according to the nerve fibers having the top thirty-three to sixty-six percent of the evaluation values.
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Specification