Arthemis: Annotation software in an integrated capturing and analysis system for colonoscopy
Computer Methods and Programs in Biomedicine
Polyp Detection in Endoscopic Video Using SVMs
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Colorectal Polyps Detection Using Texture Features and Support Vector Machine
MDA '08 Proceedings of the 3rd international conference on Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry
Texture analysis for ulcer detection in capsule endoscopy images
Image and Vision Computing
Computer-aided classification of zoom-endoscopical images using Fourier filters
IEEE Transactions on Information Technology in Biomedicine
Computer Methods and Programs in Biomedicine
Mean shift-based lesion detection of gastroscopic images
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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In this paper, we extend the application of four texture feature extraction methods proposed for the detection of colorectal lesions, into the discrimination of gastric polyps in endoscopic video. Support Vector Machines have been utilized for the texture classification task. The polyp discrimination performance of the surveyed schemes is compared by means of Receiver Operating Characteristics (ROC). The results advocate the feasibility of a computer-based system for polyp detection in video gastroscopy that exploits the textural characteristics of the gastric mucosa in conjunction with its color appearance.