Intelligent mammary gland contrast enhancement photography classification system based on information bottleneck

Abstract

The invention discloses an intelligent mammary gland contrast enhancement photography classification system based on information bottleneck. The system comprises: an image acquisition module which for acquiring mammary gland contrast enhancement photography images and corresponding benign and malignant category labels; an image preprocessing module which carries out preprocessing operation on the mammary gland contrast enhancement photographic image; a feature extraction module which extracts image features from the preprocessed mammary gland contrast enhanced photographic image; an information bottleneck module which calculates image features, benign and malignant category labels and mutual information between input images based on an information bottleneck method so as to obtain a network loss function; and an image classification module which trains a classification model based on the image features and the loss function, and obtains a benign and malignant classification result of the to-be-classified image based on the trained classification model. The problem of accurate classification of mammary gland contrast enhancement photography based on artificial intelligence is solved.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to an information bottleneck-based intelligent breast contrast-enhanced photography classification system. Background technique [0002] The statements in this section merely mention the background technology related to the present invention and do not necessarily constitute the prior art. [0003] Breast cancer accounts for a very high proportion of female cancers, which seriously threatens women's health. Clinically, there are different opinions on the pathogenesis of breast cancer, so its etiology is still unclear. The prevention of breast cancer can only be regular physical examination and screening, which shows that effective detection methods are very important for the early treatment of breast cancer. Common breast examination methods include: breast ultrasound, MRI, mammography, and breast contrast-enhanced photography. These techniques can find lesions to...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the deficiencies in the prior art, the present invention provides an intelligent mammary gland contrast-enhanced photographic classification system based on information bottleneck, which enhances the image features of two modalities and two viewing angles of photographic images through mammary gland contrast enhancement, and utilizes the information bottleneck method to Get more information related to classification, improve the accuracy of breast contrast-enhanced photography classification, and solve the problem of accurate classification of breast contrast-enhanced photography based on artificial intelligence

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