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Amygdala Spectral Clustering and Segmentation Method Based on Resting State Functional Connectivity

An amygdala, resting state technology, applied in the field of automatic segmentation of amygdala sub-brain regions, can solve the problems of low efficiency, unfavorable promotion, and long time consumption

Active Publication Date: 2019-04-09
XI AN JIAOTONG UNIV
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Problems solved by technology

On the one hand, such a segmentation method requires researchers to have a high medical anatomical background; on the other hand, it is inefficient and time-consuming, which is not conducive to promotion.

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  • Amygdala Spectral Clustering and Segmentation Method Based on Resting State Functional Connectivity
  • Amygdala Spectral Clustering and Segmentation Method Based on Resting State Functional Connectivity
  • Amygdala Spectral Clustering and Segmentation Method Based on Resting State Functional Connectivity

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Embodiment Construction

[0032] The present invention is described in detail below in conjunction with accompanying drawing.

[0033] The principle of the method for amygdala brain region segmentation based on the resting state functional connectivity of the present invention is as follows: figure 1 shown.

[0034] (1) First, preprocess the original resting-state magnetic resonance data collected. Due to the influence of various noises in the magnetic resonance scanning process, there are differences in the scale and position of the individual itself, so it is very necessary to analyze the data Do some preprocessing on the data before. In the data acquisition of the whole experiment, the main sources of noise information include: (1) physical head movement; (2) difference in scanning time between layers in the image; (3) inhomogeneity of the external magnetic field. Brain function image preprocessing is to use the brain function image and standard templates to perform affine registration transformat...

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Abstract

A spectral clustering and segmentation method of amygdala based on resting-state functional imaging is an automatic and efficient method based on the spectral clustering algorithm for the brain region based on the similarity of voxel functions inside the amygdala. State MRI data preprocessing, extraction of amygdala brain regions, calculation of whole-brain functional connectivity of voxels inside the amygdala, and finally clustering and segmentation of the functional connectivity matrix spectrum. It has a large degree of consistency, and has achieved satisfactory results in terms of stability and anti-noise interference. Compared with traditional manual segmentation methods, it is simpler, more convenient, more efficient, and more repeatable.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an amygdala spectral clustering and segmentation method based on resting-state functional connectivity, in particular to using a spectral clustering algorithm to perform amygdala sub-brain segmentation based on the similarity of the whole-brain connection pattern of each voxel of the amygdala. A method for automatic segmentation of regions. Background technique [0002] fMRI is one of the main non-invasive methods to study brain activity and brain function, with millimeter-level spatial resolution. The proposal and development of the BOLD-fMRI method has made a breakthrough in the study of brain cognitive function, and it has become an important tool for neuroscience to explore the neural mechanism of the human brain. fMRI—generally refers to magnetic resonance imaging based on blood oxygen level-dependent (BOLD), which responds to changes in magnetic resonance signals caused by ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06K9/62
CPCG06T2207/30016G06T2207/10088G06F18/22
Inventor 林盘窦顺阳王刚王雪丽
Owner XI AN JIAOTONG UNIV