Interactive brain fiber selection and visualization method

Abstract

The invention provides an interactive brain fiber selection and visualization method. The method comprises the steps that 1) brain fiber data are acquired; 2) the direction vector of each fiber is calculated; 3) the directionality of each fiber is calculated or the distribution matrix of fibers is calculated to acquire a determination condition; and 4) the determination condition is used to screen fibers to acquire a local fiber map with better space perception.

Description

technical field [0001] This article involves the study of brain nerve fibers, which is an interactive method of brain fiber selection and visualization. Background technique [0002] With the development of nuclear magnetic resonance imaging technology, non-invasive imaging technologies such as diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), and high angular resolution diffusion imaging (HARDI) have come out one after another. DWI is a method for measuring spin proton microscopic randomness. Displacement technology explores the characteristics of biological tissues by measuring the resistance of biological tissues to the Brownian motion of water molecules. DTI introduces tensors on the basis of DWI, so that it has direction information and has become a commonly used method for detecting brain white matter. The technology of fiber structure, however, the DTI model is limited by the Gaussian assumption, and can only give information about the direction of one...

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Problems solved by technology

[0002] With the development of nuclear magnetic resonance imaging technology, non-invasive imaging technologies such as diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), and high angular resolution diffusion imaging (HARDI) have come out one after another. DWI is a method for measuring spin proton microscopic randomness. Displacement technology explores the characteristics of biological tissues by measuring the resistance of biological tissues to the Brownian motion of water molecules. DTI introduces tensors on the basis of DWI, so that it has direction information and has become a commonly used method for detecting brain white matter. The technology of fiber structure, however, the DTI model is limited by the Gaussian assumption, and can only give information about the direction of one fiber in each voxel, and cannot reveal the intersection of fibers. HARDI technology is developed from DTI technology, which uses spherical Sampling, while assuming that the water molecules in the tissue are Gaussian dispersion, can be used to describe the state of fiber crossing and merging, and has attracted the attention of relevant researchers.

[0003] DTI and HARDI data can represent a group of fiber bundles. This process is called fiber tracking. Fiber tracking can display the distribution and connection relationship of brain fibers in three-dimensional space. The display of fibers is a process of dense line drawing. Brain fibers in three-dimensional space are in the Visually, there are complex and confusing problems, and it is difficult to strike a balance between fiber information and occlusion

When people observe brain fibers, the overall structure of brain fibers is often not directly observed due to the presence of many fibers on the surface, so it is difficult to explore and analyze the whole brain fibers.

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