Brain fiber clustering method based on space path similarity

Abstract

The invention discloses a brain fiber clustering method based on space path similarity. The method comprises the following steps: 1) importing fiber data, tracing a fiber path, and calculating the similarity of each fiber; 2) respectively using two different fiber clustering methods according to the fiber data volume, namely a DPC (NGK) fiber clustering method and a DPC (GK) fiber clustering method because the fiber data is diversified, fibers of one part of tissues are relatively disperse and the fiber quantity is small, and fibers of another part of tissues are relatively dense and the fiber quantity is extremely large; and 3) mapping the clustered fiber data to a corresponding color space, and performing color encoding and visualized display, thereby achieving the effect of obviously distinguishing different types of fibers.

Description

Technical field [0001] The invention relates to the study of brain nerve fibers, and is a brain fiber clustering method based on spatial path similarity. Background technique [0002] The dispersion of water molecules is the basis of nuclear magnetic resonance technology. DWI, DTI and HARDI non-invasive detection technologies are all developed on the basis of dispersion and diffusion of water molecules. Through MRI technology, people can already track the direction of brain white matter fibers. DTI is the most commonly used MRI technique to detect the white matter structure of the brain, but its model is limited by Gaussian hypothesis and cannot solve the problem of multi-fiber crossing. HARDI technology describes the displacement process of water molecules as a mixture of Gaussian models, and compensates for the shortcomings of DTI technology by calculating the characteristic direction and characteristic value of the dispersion tensor of each component. Can better describe the...

AI Technical Summary

Problems solved by technology

Through the tracking of fibers, people have been able to obtain thousands of fibers in the brain. However, these fibers are intricate and obstruct each other, and people cannot directly observe the organizational structure of brain fibers with the naked eye.

Due to the complexity of fibers, people cannot visualize and analyze fiber trajectories well. How to cluster and render a large number of fiber trajectories is still a very important issue.

Images