Novel genotype analysis method based on multimodal brain images

A genotype analysis and brain imaging technology, applied in the intersection of digital image analysis and pattern recognition, medical imaging and computer science, can solve the problem of ignoring node connection information, and achieve the effect of good prediction results

Inactive Publication Date: 2017-12-22
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0003] Most of the current research work focuses on the association analysis between neuroimaging and gene variation based on bra...

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  • Novel genotype analysis method based on multimodal brain images
  • Novel genotype analysis method based on multimodal brain images
  • Novel genotype analysis method based on multimodal brain images

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Embodiment Construction

[0022] In the following, 40 cases of Alzheimer's patients and normal people are selected, and the above-mentioned method of the present invention will be described in detail with reference to FIG. 1 . Among them, the age, gender, and years of education of the subjects are shown in Table 1 below. This paper adopts the leave-one-out (LOO) method for cross-validation, that is, one sample is reserved each time as the test data, and the remaining samples are used as training samples to train the regression model. A total of 64 cross-validations are performed, and finally 64 predictions are taken. The average of the results was taken as the final result.

[0023] Table 1 Statistical table of subject information

[0024]

[0025] The overall process of the present invention is shown in Figure 1. The specific implementation process includes five steps:

[0026] The first step is to preprocess the brain fMRI images of all samples and construct the brain connection network. We us...

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Abstract

The invention discloses a novel genotype analysis method based on multimodal brain images. With utilization of information, including a structural image and a functional image, of two kinds of modes, regression on the rs429358 locus genotype linked to the Alzheimer's disease closely is realized. The method comprises: extracting voxel features from a brain structure images and extracting connecting network features from a brain function image; carrying out feature extraction on the two kinds of features by using an elastic network and keeping brain area and network connection with a high association degree; and then carrying out fusion and genotype regression on selected nodes and side attributes by using a multi-kernel support vector. The method has the following advantages: for the brain image with the complicated structure and functions and genotype data, a novel regression analysis method for a single locus genotype based on structural and functional multimodal brain images is put forward; the analysis effect is good; and complementary information of the two modes is utilized fully.

Description

technical field [0001] The invention discloses a genotype analysis method based on multimodal brain images. The invention belongs to the cross field of medical images and computer science, and relates to the technical field of digital image analysis and pattern recognition. Background technique [0002] With the rapid development of medical imaging technology, genetic imaging has become an emerging scientific field, which mainly studies the influence of gene variation on brain structure and function. For Alzheimer's disease, genetic factors play an important regulatory role. At present, there is evidence that APOE (apolipoprotein E) ε 4 genes are highly correlated with the onset of Alzheimer's disease. The regulatory mechanism of genetic variation on organisms is complex and unknown, and single nucleotide polymorphisms (singlenucleotide polymorphisms, SNPs) are a common biological genetic marker. Since the brain of Alzheimer's disease patients will have structural atrophy...

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Application Information

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IPC IPC(8): G06T7/00G06T7/30G06F19/00
CPCG06T7/0012G06T7/30G06T2207/10088G06T2207/20081G06T2207/20104G06T2207/30016
Inventor 张道强李蝉秀
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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