Affiliation:
1. Women’s Hospital School of Medicine, ZheJiang University, Hangzhou 310000, China
Abstract
Endoscopic diagnosis is an important means for gastric polyp detection. In this paper, a panoramic image of gastroscopy is developed, which can display the inner surface of the stomach intuitively and comprehensively. Moreover, the proposed automatic detection solution can help doctors locate the polyps automatically and reduce missed diagnosis. The main contributions of this paper are firstly, a gastroscopic panorama reconstruction method is developed. The reconstruction does not require additional hardware devices and can solve the problem of texture dislocation and illumination imbalance properly; secondly, an end-to-end multiobject detection for gastroscopic panorama is trained based on a deep learning framework. Compared with traditional solutions, the automatic polyp detection system can locate all polyps in the inner wall of the stomach in real time and assist doctors to find the lesions. Thirdly, the system was evaluated in the Affiliated Hospital of Zhejiang University. The results show that the average error of the panorama is less than 2 mm, the accuracy of the polyp detection is 95%, and the recall rate is 99%. In addition, the research roadmap of this paper has guiding significance for endoscopy-assisted detection of other human soft cavities.
Funder
Medical Scientific Research Foundation of Zhejiang Province
Subject
Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modelling and Simulation,General Medicine
Cited by
4 articles.
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