Wireless capsule endoscope-based computer-aided detection system and detection method for pathological changes in small intestine

Abstract

The invention discloses a wireless capsule endoscope small intestine lesion computer auxiliary detection system and method. At present, the technology of the capsule endoscope in the aspect of intelligent lesion identification and accurate positioning is very limited. The data input module is used for acquiring the video data of the wireless capsule endoscope of the patient, and an image of the capsule endoscope is obtained by extracting a video frame technology; the image preprocessing module is used for preprocessing the image of the wireless capsule endoscope, the small intestine image recognition module is used for recognizing and extracting a small intestine image and an image sequence in the preprocessed capsule endoscope image; the small intestine lesion analysis and positioning module is used for identifying and classifying the small intestine lesion and extracting the specific position of the focus; the user interaction module forms an auxiliary diagnosis result according to the small intestine lesion information and the analysis result of the positioning module, and the doctor can confirm, modify or input the medical advice so as to form a diagnosis report. According to the invention, the practical value of the capsule endoscope in clinic is promoted, so that a more efficient and more standard diagnosis mode is formed.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a computer-aided detection system and detection method for small intestine lesion images under a wireless capsule endoscope. Background technique [0002] With the continuous acceleration of the industrialization process of cities in today's society, people's pace of life is also accelerating, work pressure continues to increase, and psychological pressure is also increasing day by day, which leads to an increase in the incidence of digestive tract diseases year by year. Gastrointestinal diseases and cancers caused by further deterioration (such as intestinal cancer, gastric cancer, esophageal cancer, etc.) are one of the biggest killers of national health (accounting for about 50-60% of the incidence of all malignant tumors in my country), seriously affecting people's normal life. Life. Studies have shown that early detection and treatment of gastrointestinal disease is...

AI Technical Summary

Problems solved by technology

These several schemes have several common shortcomings: (1) only for a single lesion image, bleeding or hookworm disease; (2) using traditional feature extraction and classification methods to realize automatic recognition of certain lesion images Automatic learning of lesion features, so invisible features of images cannot be obtained, which affects the accuracy of classification results and also affects the universality of the algorithm

The artificial feature extraction method used in this method has problems such as long time consumption, poor stability and universal applicability, which greatly affects the accuracy of classification results.

In addition, none of the above disclosed technologies involve the segmentation and labeling of the lesion location, and the realization of the labeling of the lesion location will further promote the doctor's diagnosis of the disease

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