Impact of Visual Features on the Segmentation of Gastroenterology Images Using Normalized Cuts

• Type: Article in International Scientific Journal
• Date: 2013

Authors

Farhan Riaz (Author) Other; Francisco Baldaque Silva (Author) Other; Mario Dinis Ribeiro (Author) Other; Miguel Tavares Coimbra (Author) FCUP

Journal

Title: IEEE Transactions on Biomedical Engineering

Vol. 60

Pages: 1191-1201

ISSN: 0018-9294

Publisher: IEEE

Indexing

ISI Web of Knowledge - 15 Citations

Scopus - 21 Citations

Scientific classification

FOS: Engineering and technology > Environmental biotechnology

Other information

Authenticus ID: P-005-182

DOI: 10.1109/tbme.2012.2230174

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11