Esophageal cancer preoperative management method and system based on artificial intelligence

Abstract

The invention relates to the technical field of medical assistance, in particular to an esophageal cancer preoperative management method and system based on artificial intelligence. The system comprises a client and a server. The server comprises a case typical picture library, a picture pattern recognition module, a high-risk lesion target recognition module, a surface blood vessel typing recognition module and an AVA segmentation recognition module. According to the method, a plurality of deep learning models (relating to image classification, target detection and semantic segmentation) areconstructed according to different tasks, a cascaded model fusion technology is adopted, and a full-process intelligent auxiliary diagnosis function is provided in the esophageal disease screening process of an endoscopic doctor. The esophagus high-risk focus is detected in the NBI distant view mode, and AB typing and AVA typing are observed according to endoscopic examination, so that doctors canbe helped to better and accurately evaluate the illness state of a patient, and more scientific treatment options are provided.

Description

technical field [0001] The present invention relates to the field of medical assistance technology, in particular to a method and system for preoperative management of esophageal cancer based on artificial intelligence. Background technique [0002] Esophageal cancer is a malignant tumor that occurs in the epithelium of the esophageal mucosa. About 300,000 people in the world die of esophageal cancer every year. China is an area with a high incidence of esophageal cancer. About 48% of the world's esophageal cancer occurs in China, and at the same time, about 49% of the world's dead patients are in China. In China, more than 90% of esophageal cancers are squamous cell carcinomas, and the incidence is high in rural and economically backward areas; about 75% of patients are locally advanced or advanced esophageal cancers, and the 5-year survival rate is less than 20%. After 5 years, the survival rate can reach more than 90%. From this point of view, early diagnosis and treatm...

AI Technical Summary

Problems solved by technology

[0005] Based on the technical problems existing in the background technology, the present invention proposes a method and system for preoperative management of esophageal cancer based on artificial intelligence, which can detect high-risk esophageal lesions, and further detect esophageal tumor lesions AB in the ME-NBI mod

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