Impact of visual features on the segmentation of gastroenterology images using normalized cuts

Riaz, Farhan, Silva, Francisco Baldaque, Ribeiro, Mario Dinis and Coimbra, Miguel Tavares (2013) Impact of visual features on the segmentation of gastroenterology images using normalized cuts. IEEE Transactions on Biomedical Engineering, 60 (5). pp. 1191-1201. ISSN 0018-9294

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Item Type:Article
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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.

Keywords:feature extraction, Image segmentation, Gastroenterology, Image color analysis, Imaging, Image edge detection, Visualization
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:52399
Deposited On:18 Nov 2022 11:53

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