Diagnosis system of thyroid ultrasound image nodules based on multi-scale convolutional neural network

Abstract

The present invention provides an automatic diagnosis system for nodules in thyroid ultrasound images based on multi-scale convolutional neural networks, including: a nodule classification module for thyroid nodules from coarse to fine, an automatic detection module for thyroid nodule regions, and a fine classification module for thyroid nodules ; The convolutional neural network of multi-scale feature fusion extracts the features of the size of different perception areas, so as to combine the local and global information to extract the contextual semantic features of nodules to automatically locate thyroid nodules. The present invention can accurately predict the location of lesions and the probability of occurrence of benign and malignant lesions through the feature extraction of multi-scale coarse-to-fine neural networks and the design of multi-scale fine classification AlexNet with pyramid structure, and can assist doctors in the diagnosis of thyroid lesions. Improving the objectivity of diagnosis, it has the characteristics of good real-time performance and high accuracy rate.

Description

technical field [0001] The invention relates to an automatic diagnosis system for thyroid ultrasound image nodules based on a multi-scale convolutional neural network, which belongs to the field of deep learning and auxiliary medical treatment. Background technique [0002] In the 1940s, ultrasound imaging technology began to be used clinically, and in 1962, it began to diagnose the thyroid gland. Thyroid ultrasound imaging technology can provide doctors with information about the tissue of the thyroid gland, and has become the preferred technical diagnostic method for modern doctors. [0003] Convolutional neural network technology has had a research history of more than 30 years since the 1980s. Convolutional neural network was first applied to handwritten digit recognition. In the field of computer vision, recognition of faces and objects has always been A very challenging research hotspot. In recent years, with the development of the Internet, the acquisition of a larg...

AI Technical Summary

Problems solved by technology

However, at present, due to the characteristics of low contrast, inconspicuous borders, and small visual differences in ultrasound images, the research on ultrasound images of the thyroid still faces many challenges, because there are more complex physical and visual feature mechanisms behind these phenomena. Convincing simulation effects require the support of multi-disciplinary interdisciplinary theory and efficient algorithm design combining software and hardware

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