Method for processing multi-mode brain nerve image characteristics

A feature selection method and multi-modal technology, applied in the fields of radiological diagnostic equipment, medical science, diagnosis, etc., can solve the problems of unexplainable brain image features, subject injury, and insufficient multi-modal brain Issues such as neuroimaging feature data

Active Publication Date: 2019-05-21
HEBEI UNIV OF TECH
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Problems solved by technology

The method of the present invention overcomes that in the existing detection and analysis of Alzheimer's disease technology, the existing biomarker characteristics will cause harm to the subject, and only one kind of brain image character

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  • Method for processing multi-mode brain nerve image characteristics
  • Method for processing multi-mode brain nerve image characteristics
  • Method for processing multi-mode brain nerve image characteristics

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Embodiment 1

[0092] The processing method of the multimodal brain neuroimaging features of this embodiment is to use the multimodal neuroimaging feature selection method of SWLRC to mine biomarkers, and then use the multi-kernel SVM method for classification. The specific steps are as follows:

[0093] The first step, multimodal neuroimaging input:

[0094] Region-of-interest template features were extracted from voxel-based morphometry-processed magnetic resonance brain images and fluorodeoxyglucose-positron emission tomography brain images of two modality brain images by first using statistical parametric mapping The software package registers voxel-based morphometrically processed magnetic resonance brain images and fluorodeoxyglucose-positron emission tomography brain images into a standard space, and then uses the toolbox MarsBaR of the SPM software for 116 regions of interest to automatically The anatomical marker template uses the gray density value of the magnetic resonance brain i...

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Abstract

The invention discloses a method for processing multi-mode brain nerve image characteristics, and relates to image preprocessing for extracting image characteristics or features of a recognition figure. The method comprises the following steps of: firstly, performing characteristic selection on multi-mode data by adopting a multi-mode nerve image characteristic selection method with sample weightand low rank constraint to obtain a low-dimensional characteristic matrix, calculating a nuclear matrix of each mode to obtain a low-dimensional characteristic matrix, calculating a nuclear matrix ofeach mode, fusing the nuclear matrices of different modes into a nuclear matrix to select more discriminative biomarker characteristics. New Alzheimer disease sample cases are predicted and classifiedby using a multi-core support vector machine. The defects that, in the prior art, a subject can be injured by using biomarker characteristics, an illness brain area of a patient cannot be found by only using one kind of brain image characteristic data or not fully utilizing the multi-mode brain nerve image characteristics, and the characteristics in the used brain image are free of medical explanation are solved.

Description

technical field [0001] The technical solution of the present invention relates to the image preprocessing for the extraction of image features or characteristics for recognition graphics, in particular, a processing method for multimodal brain neuroimage features. Background technique [0002] Alzheimer's disease is a difficult to cure and irreversible brain disease. At this stage, drugs for the treatment of Alzheimer's disease have limited effects, so it is very important to intervene in the early stage of the disease. With the development of neuroimaging technology, a variety of images reflecting human brain conditions have been obtained through different technical means, such as magnetic resonance images or positron emission tomography scans. Doctors use the acquired knowledge and practical experience to interpret the anatomical structure and pathophysiological information reflected in the patient's brain image. However, this method of artificially interpreting the patien...

Claims

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Application Information

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IPC IPC(8): A61B6/00
Inventor 郭迎春包永进郝小可刘依于洋朱叶师硕阎刚
Owner HEBEI UNIV OF TECH
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