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Authors: Arnaud A. A. Setio 1 ; Fons van der Sommen 1 ; Svitlana Zinger 1 ; Erik J. Schoon 2 and Peter H. N. de With 1

Affiliations: 1 Eindhoven University of Technology, Netherlands ; 2 Catharina Hospital, Netherlands

ISBN: 978-989-8565-47-1

Keyword(s): HD Endoscopy, Cancer Detection, Esophageal Irregularities, Co-occurance Matrix, Texture Spectrum Histogram (TSH), Rotation Invariant Uniform Local Binary Patterns (RIULBP), Gabor Features.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Medical Image Applications

Abstract: Esophageal cancer is the fastest rising type of cancer in the Western world. The novel technology of High Definition (HD) endoscopy enables physicians to find texture patterns related to early cancer. It encourages the development of a Computer-Aided Decision (CAD) system in order to help physicians with faster identification of early cancer and decrease the miss rate. However, an appropriate texture feature extraction, which is needed for classification, has not been studied yet. In this paper, we compare several techniques for texture feature extraction, including co-occurrence matrix features, LBP and Gabor features and evaluate their performance in detecting early stage cancer in HD endoscopic images. In order to exploit more image characteristics, we introduce an efficient combination of the texture and color features. Furthermore, we add a specific preprocessing step designed for endoscopy images, which improves the classification accuracy. After reducing the feature dimensional ity using Principal Component Analysis (PCA), we classify selected features with a Support Vector Machine (SVM). The experimental results validated by an expert gastroenterologist show that the proposed feature extraction is promising and reaches a classification accuracy up to 96.48%. (More)

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Paper citation in several formats:
A. A. Setio A., van der Sommen F., Zinger S., Schoon E. and de With P. (2013). Evaluation and Comparison of Textural Feature Representation for the Detection of Early Stage Cancer in Endoscopy.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 238-243. DOI: 10.5220/0004204502380243

@conference{visapp13,
author={Arnaud {A. A. Setio} and Fons {van der Sommen} and Svitlana Zinger and Erik J. Schoon and Peter H. N. {de With}},
title={Evaluation and Comparison of Textural Feature Representation for the Detection of Early Stage Cancer in Endoscopy},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={238-243},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004204502380243},
isbn={978-989-8565-47-1},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Evaluation and Comparison of Textural Feature Representation for the Detection of Early Stage Cancer in Endoscopy
SN - 978-989-8565-47-1
AU - A. A. Setio A.
AU - van der Sommen F.
AU - Zinger S.
AU - Schoon E.
AU - de With P.
PY - 2013
SP - 238
EP - 243
DO - 10.5220/0004204502380243

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