title: Impact of visual features on the segmentation of gastroenterology images using normalized cuts.
abstract: Gastroenterology imaging is an essential tool to detect gastrointestinal cancer in patients. Computer-assisted diagnosis is desirable to help us improve the reliability of this detection. However, traditional computer vision methodologies, mainly segmentation, do not translate well to the specific visual characteristics of a gastroenterology imaging scenario. In this paper, we propose a novel method for the segmentation of gastroenterology images from two distinct imaging modalities and organs: chromoendoscopy (CH) and narrow-band imaging (NBI) from stomach and esophagus, respectively. We have used various visual features individually and their combinations (edgemaps, creaseness, and color) in normalized cuts image segmentation framework to segment ground truth datasets of 142 CH and 224 NBI images. Experiments show that an integration of edgemaps and creaseness in normalized cuts gives the best segmentation performance resulting in high-quality segmentations of the gastroenterology images.
authors.affiliation: Instituto de Telecomunicações, Department of Computer Science, Faculdade de Ciencias da Universidade do Porto, 4169-007 Porto, Portugal. farhan.riaz@dcc.fc.up.pt
authors.forename: Farhan
authors.initials: F
authors.lastname: Riaz
authors.forename: Francisco Baldaque
authors.initials: FB
authors.lastname: Silva
authors.forename: Mario Dinis
authors.initials: MD
authors.lastname: Ribeiro
authors.forename: Miguel Tavares
authors.initials: MT
authors.lastname: Coimbra
mesh_terms: D000465:Algorithms; D001471:Barrett Esophagus / Q000473:pathology; D016000:Cluster Analysis; D016208:Databases, Factual; D016145:Endoscopy, Digestive System / Q000379:methods*; D041981:Gastrointestinal Tract / Q000033:anatomy & histology / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D062048:Narrow Band Imaging / Q000379:methods; D013274:Stomach Neoplasms / Q000473:pathology