Thalamus function partitioning method based on subspace feature learning

Abstract

The invention discloses a thalamus function partitioning method based on subspace feature learning. The thalamus function partitioning method comprises the following steps: firstly, carrying out fibertracking by using diffusion tensor imaging to obtain internal structure connection information of the brain of a living body, and extracting complex nonlinear thalamus cortex features by using fine cortex partitions to form structure connection features; then, using the deep subspace network and the hidden subspace mapping of the added self-expression feature learning features to extract low-dimensional subspace characteristics; and finally, performing spatial constraint on voxel features to reduce the influence of noise, better reflecting a spatial topological structure, enriching the extraction of spatial information, constructing an affinity matrix, and obtaining functional partitions by using a normalized segmentation method. According to the thalamus function partitioning method, theinfluence of noise can be reduced, and the topological structure of voxel space can be better reflected, and extraction of space information is enriched, and thalamus function partitions can be efficiently obtained.

Description

technical field [0001] The invention belongs to the field of digital images, in particular to a thalamus function partition method based on subspace feature learning. Background technique [0002] In recent years, medical imaging techniques have provided new avenues for the non-invasive construction of thalamic functional partitions. Diffusion tensor imaging is based on measuring the diffusion properties of water molecules in brain tissue to obtain tissue information, and can reconstruct fiber bundles to characterize the structural connections between different regions. Diffusion refers to the random and irregular movement of molecules, which can be divided into isotropy and anisotropy based on the degree of diffusion of molecules in a specific direction in space. Isotropy means that the chances of molecules moving in all directions are equal. For example, in pure water, the dispersion of water molecules is isotropic and the diffusion of water molecules in brain gray matter...

AI Technical Summary

Problems solved by technology

However, using other voxels in the whole brain to calculate the connection feature data of thalamic voxels is too high and is easily affected by noise.

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