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Method for achieving white matter rapid segmentation and fiber cluster data analysis

A technology for brain white matter and data analysis, applied in the field of medical image processing, can solve problems such as long time consumption, achieve the effect of reducing calculation amount, relatively long time-consuming solution, and ensuring classification accuracy

Inactive Publication Date: 2016-10-12
DALIAN UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the relatively long time-consuming problem of the prior art, the present invention proposes a method for fast segmentation of brain white matter and data analysis of fiber clusters

Method used

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  • Method for achieving white matter rapid segmentation and fiber cluster data analysis
  • Method for achieving white matter rapid segmentation and fiber cluster data analysis
  • Method for achieving white matter rapid segmentation and fiber cluster data analysis

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Embodiment 1

[0038] 1. Data preprocessing of young children's brain fiber clusters. Such as figure 1 As shown, the brain fiber cluster data is preprocessed. Use existing medical image processing tools (for example: Mricron, DTIstudio, FSL, DiffeoMap) to transform the data of young children’s brain fiber clusters into expressions that can participate in clustering operations. In the experiment, let p=10, that is, each fiber is divided into 9 segments, ten nodes are found, and the positions of these ten nodes are recorded as the representation of the fiber.

[0039] 2. Segmentation (use our proposed Fast density-peaks clustering for fiber clustering and segmentation).

[0040] 2-1. Calculate the distance between every two fibers to obtain the distance matrix distMat.

[0041] 2-2. Such as image 3 The method shown draws on the idea of ​​a binary tree. First, the calculated distance between a certain fiber i and other fibers is combined into a data set A, and the median or mean value of the data i...

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Abstract

The invention discloses a method for achieving white matter rapid segmentation and fiber cluster data analysis. The method replaces all fiber distance data problem by neighbor fiber distance data so as to achieve algorithm acceleration, wherein adjacent fiber search uses a binary tree method so as to obviously reduce the calculated quantity of fiber density [rho] and factor dc. The method solves long time consumed in the prior art and well guarantee classification accuracy.

Description

Technical field [0001] The invention belongs to the field of medical image processing, and relates to clustering processing and data analysis of brain fiber clusters, and in particular to a method for rapid clustering of brain fiber clusters based on peak density. Background technique [0002] Fiber cluster clustering is an indispensable link in the field of medical image processing research, and it is also an important technology that makes medical image analysis more convenient. The fiber clusters of different structures in the brain correspond to different functions, and medical analysis also corresponds to some differences. A clustering algorithm that can correctly segment fiber clusters and classify and distinguish fiber clusters of different structures is the basis and guarantee for the correct analysis of corresponding functions in subsequent medicine. [0003] At present, there are many effective algorithms in the field of clustering algorithms, such as K-means, GMM, and m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0012G06T2207/30016G06F18/24147
Inventor 樊鑫罗钟铉程世超段煜茁王倩
Owner DALIAN UNIV OF TECH
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