Magnetic resonance diffusion tensor imaging fiber bundle tracking device

Abstract

The invention relates to a magnetic resonance diffusion tensor imaging fiber bundle tracking device. The process is respectively completed by each component through the following steps of (1) collecting magnetic resonance diffusion tensor images; (2) carrying out brain issue dividing on a sequence without a diffusion gradient magnetic field and any sequence with the diffusion gradient magnetic field, and using the sequence without the diffusion gradient magnetic field as an image reference template of the brain tissues; (3) carrying out three-dimensional affine conversion on the two image sequences of the brain tissues after being extracted, to obtain a space conversion relationship; (4) carrying out space conversion on the remained diffusion tensor images by an optimum conversion relationship; (5) calculating tensor fields and feature vectors; (6) setting the interested areas and tracking conditions; and (7) carrying out the bidirectional tracking and displaying based on a fiber bundle with variable step size, so as to quickly and effectively carry out fiber bundle tracking and displaying on the white matters of human brain. In the diffusion tensor imaging process, the image deviation caused by space positions can be corrected, and the elastic step size is adopted in the tracking process, so as to ensure the reliable fiber bundle tracking.

Description

technical field [0001] The invention relates to a magnetic resonance diffusion tensor imaging fiber bundle tracking device which is used to solve the problem of displaying white matter fiber bundles in human brain magnetic resonance diffusion tensor imaging and can be applied to the fields of clinical diagnosis and treatment of human brain diseases and the like. Background technique [0002] Due to the different acquisition times of multi-sequence images of magnetic resonance diffusion tensor imaging, the spatial positions of the sequence images are prone to inconsistency, which leads to errors in the tensor of each voxel, and ultimately makes it difficult to achieve satisfactory results in white matter fiber tract tracking. Even if a head fixation device is used in the actual scanning process, the head movement cannot be completely eliminated, so the spatial position correction of the multi-sequence images is very important. In the process of tracing brain nerve fiber bundl...

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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the existing technology cannot complete the magnetic resonance diffusion tensor imaging fiber tract tracking with high precision, and provides a method for performing magnetic resonance diffusion tensor imaging according to the results of brain function image acquisition equipment scanning the human brain. The magnetic resonance diffusion tensor imaging fiber tract tracking device for imaging fiber tract tracking includes: collecting different sequences of magnetic resonance diffusion tensor images of the human brain in at least twelve directions through the acquisition matrix from the brain function image acquisition equipment, taking different Any sequence in the sequence of MRI diffusion tensor images is used as the acquisition part of the reference image; normalization processing is performed on different sequence MRI diffusion tensor images so that the pixel size and geometric size of all sequence MRI diffusion tensor images are the same Consistent normalization processing part; the reference image is extracted and segmented to obtain the corresponding segmentation part of the reference brain tissue image of the sequence without applying the diffuse magnetic field and the brain tissue image to be corrected of the sequence of applying the diffuse gradient magnetic field. The tissue image is used as a standard brain tissue template; the spatial transformation relationship between the reference brain tissue image of the reference image and the brain tissue image to be corrected is calculated according to the spatial transformation matrix, and the reference brain tissue image is used as the brain tissue standard template to realize the reference brain tissue image of the reference image. The pixels of the tissue image and the pixels of the brain tissue image to be corrected reach a one-to-one corresponding reference image correction part in spatial position; all sequence magnetic resonance diffusion tensor images except the reference image are formed into corresponding images to be corrected, and according to the spatial transformation The relationship is to perform a three-dimensional affine transformation on the image to be corrected so that the pixels of all the sequential magnetic resonance diffusion tensor images reach a one-to-one corresponding image registration correction part in the spatial position; the matrix is ​​used to calculate all the sequential magnetic resonance diffusion tensor images. The tensor field and the diffusion information of each voxel in all sequential magnetic resonance diffusion tensor images are represented by a 3×3 matrix tensor, and the matrix decomposition of each voxel is performed to obtain the eigenvalue and eigenvector of each voxel Department of Computing

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