NDLI: Segmentation for classification of gastroenterology images

Content Provider	IEEE Xplore Digital Library
Author	Coimbra, M. Riaz, F. Areia, M. Silva, F.B. Dinis-Ribeiro, M.
Copyright Year	2010
Description	Author affiliation: Karolinska Universitessjukhuse, Sweden (Silva, F.B.) \|\| Instituto de Telecomunicações, Department of Computer Science, Faculdade de Ciências da Universidade do Porto, Portugal (Coimbra, M.; Riaz, F.) \|\| CINTESIS/Faculdade de Medicina da Universidade do Porto, Portugal (Dinis-Ribeiro, M.) \|\| Portuguese Institute of Oncology - Coimbra, Portugal (Areia, M.)
Abstract	Automatic classification of cancer lesions in tissues observed using gastroenterology imaging is a non-trivial pattern recognition task involving filtering, segmentation, feature extraction and classification. In this paper we measure the impact of a variety of segmentation algorithms (mean shift, normalized cuts, level-sets) on the automatic classification performance of gastric tissue into three classes: cancerous, pre-cancerous and normal. Classification uses a combination of color (hue-saturation histograms) and texture (local binary patterns) features, applied to two distinct imaging modalities: chromoendoscopy and narrow-band imaging. Results show that mean-shift obtains an interesting performance for both scenarios producing low classification degradations (6%), full image classification is highly inaccurate reinforcing the importance of segmentation research for Gastroenterology, and confirm that Patch Index is an interesting measure of the classification potential of small to medium segmented regions.
Starting Page	4744
Ending Page	4747
File Size	1119278
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626622
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Classification algorithms Imaging Manuals Gastroenterology Image color analysis Feature extraction
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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