The Computer-aided Diagnostics of Gastric Lesions by using High Definition Narrow-band Imaging Endoscopy and Real-time Pattern Recognition System

摘要

High Definition (HD) and Magnified Narrow band imaging endoscopy (ME-NBI) allowed to recognize types of gastric lesions according modified VS-classification by professor Yao K., because the parameters to describe regular or irregular vascular or micro surface pattern and demarcation line in lesions were formalized. In this work endoscopic differential criteria of benign and neoplastic epithelial lesions of stomach were obtained. Based on them classification algorithm for the real-time processing of narrow-band endoscopic images with a highly productive distributed intellectual analytic decision support system for multiscale endoscopic diagnostics is presented. We also created the electronic atlas and database to collect high resolution endoscopic images, applied and proved the differential diagnosis of gastric lesions through the computer analysis. The algorithm consistently used scale-invariant feature transform detector, computation of gastric mucosa pit-pattern skeletons, "Bag of visual words" method, and K-means method for key points clustering. Resulting classification algorithm is completely automated, performed real-time analysis, and did not require preliminary selection of interest area. Image classification accuracy was 85%.