Fiber classification method based on spatial similarity and system realizing fiber classification method

Abstract

The invention provides a fiber classification method based on spatial similarity and a system realizing the fiber classification method. The fiber classification method comprises the following steps that: a data processing and fiber tracking module is adopted, and data importing, voxel modeling and probabilistic fiber outlet path tracking are carried out; a color coding, spatial mapping and fiber clustering module is adopted, and fiber beams are subjected to color coding in the spatial direction; and an interaction module is adopted, and the fiber is redrawn. The system realizing the fiber classification method comprises the data processing and fiber tracking module, the color coding, spatial mapping and fiber clustering module and the interaction module used for redrawing the fiber.

Description

technical field [0001] The present invention relates to the study of brain fibers, and is a fiber classification method and system based on spatial similarity Background technique [0002] DW-MRI (diffusion weighted magnetic resonance imaging) is currently the only non-invasive diagnostic technique in the field of in vivo white matter fiber structure research and brain connectivity exploration. By tracking the diffusion movement of water molecules in organisms, this method can visually display the fiber connections between brain functional areas, which has attracted the attention of neurosurgery researchers. [0003] To track the fiber orientation, the diffusion tensor imaging (DTI) method was proposed to estimate the diffusion probability distribution of water molecules. In view of the defects of the DTI method itself, in a voxel where multiple fibers intersect, DTI cannot fully express the direction information of multiple fibers. However, the High Angular Resolution Dif...

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Problems solved by technology

Probabilistic tracking results are not all reliable, some fi...

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