Method for processing multi-mode brain nerve image characteristics

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...

AI Technical Summary

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 characteristic data is used or insufficient utilization is used. The multimodal brain neuroimaging feature data cannot identify the patient's diseased brain region, and the features in the utilized brain image have no medical interpretation flaws

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