Digestive tract disease auxiliary diagnosis system based on deep learning

Abstract

The invention provides a digestive tract disease auxiliary diagnosis system based on deep learning. The system comprises an endoscope part judgment module for transmitting a digestive tract part imagereal-timely obtained in an endoscope operation process to a digestive tract part recognition model, and real-timely outputting the part of an endoscope in the digestive tract; a lesion area positioning module for inputting the digestive tract part image real-timely obtained in the endoscope operation process into a digestive tract lesion area recognition model, recognizing a lesion area, and marking the lesion area; and a digestive tract disease type judgment module for receiving a confocal laser microendoscope image real-timely acquired by a confocal laser microendoscope associated with theendoscope, inputting the confocal laser microendoscope image into a digestive tract disease type recognition model, comparing the part corresponding to the obtained confocal disease type with the maximum probability with the current part of the endoscope, and outputting the current digestive tract disease type and the corresponding probability thereof when the two parts are consistent.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, and in particular relates to an auxiliary diagnosis system for digestive tract diseases based on deep learning. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] According to the 2018 global cancer statistics, 4 of the top 10 tumors with the highest incidence rate come from the digestive tract. Gastrointestinal diseases, including benign, precancerous and malignant diseases of the digestive tract, are seriously threatening the quality of life and life safety of patients, causing a huge health burden. Early diagnosis and treatment can improve the prognosis of patients and save medical resources problem needs to be resolved urgently. With the development and popularization of medical imaging equipment, gastrointestinal diseases can usually be foun...

AI Technical Summary

Problems solved by technology

[0004] However, the inventors have found that the following problems still exist in the processing of medical images formed by medical imaging equipment: (1) In the face of exponentially increasing medical images, manual inspection is slow and inefficient, and missed diagnoses occur from time to time

(2) Although pathological biopsy is currently the gold standard for the diagnosis of gastrointestinal diseases, targeted biopsy, improving the efficiency of biopsy, and minimizing the number of biopsies have gradually become the trend of medical development; The number is large and misdiagnosis occurs from time to time

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