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An intelligent system for automatic detection of gastrointestinal adenomas in video endoscopy
Authors:Iakovidis Dimitris K  Maroulis Dimitris E  Karkanis Stavros A
Affiliation:Department of Informatics and Telecommunications, University of Athens, Panepistimiopolis, Illisia, 15784 Athens, Greece. rtsimage@di.uoa.gr
Abstract:Today 95% of all gastrointestinal carcinomas are believed to arise from adenomas. The early detection of adenomas could prevent their evolution to cancer. A novel system for the support of the detection of adenomas in gastrointestinal video endoscopy is presented. Unlike other systems, it accepts standard low-resolution video input thus requiring less computational resources and facilitating both portability and the potential to be used in telemedicine applications. It combines intelligent processing techniques of SVMs and color-texture analysis methodologies into a sound pattern recognition framework. Concerning the system's accuracy this was measured using ROC analysis and found to exceed 94%.
Keywords:Biomedical system   Video endoscopy   Color-texture features   Support vector machines   Gastrointestinal lesions   Adenomas
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