Alzheimer's disease classification method based on depth neural network and multi-mode images

Abstract

The invention discloses an Alzheimer's disease classification method based on a depth neural network and multi-mode images, and the method comprises the steps: taking the 2D and 3D forms of the images of N classes of Alzheimer's diseases as the input layer, taking the probability of a classification result as the output layer, and constructing a depth neural network; carrying out the preprocessing of the images of N known classes, and obtaining a training sample; training the depth neural network through the training sample, optimizing the weight of network connection, and obtaining a final depth neural network; inputting the preprocessed to-be-classified image into the final depth neural network, and outputting a classification result. In order to make the most of the feature information of the brain of an AD patient, the method introduces the multi-mode image information: an MRI image, a PET image and a DTI image on the basis of a conventional single-mode medical image classification method, and the method achieves the fusion of non-image feature CSF information and gene information.

Description

technical field [0001] The present invention relates to the field of classification and prediction of medical images, in particular to a classification method for Alzheimer's disease based on deep neural network and multimodal images, which is used to classify and predict medical images related to Alzheimer's disease by using deep neural network . Background technique [0002] Today, with the vigorous development of image processing technology, pattern recognition and machine learning theories and methods, medical image processing, as one of the fields most closely related to human life, has attracted more and more attention following in the footsteps of artificial intelligence. The classification of Alzheimer's Disease (AD) is an important branch in the field of medical image classification. It is of great significance in the computer-aided diagnosis of AD, especially for the early diagnosis of the disease and the timely control of the deterioration of the disease. Mild co...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a classification method for Alzheimer's disease based on deep neural network and multi-modal images, which solves the difficulty and inadequacy of feature extraction in the classification of Alzheimer's disease by existing machine learning classification methods. Comprehensive, technical issues leading to low classification accuracy

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