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Proceedings Paper

A content-based image retrieval method for optical colonoscopy images based on image recognition techniques
Author(s): Hirokazu Nosato; Hidenori Sakanashi; Eiichi Takahashi; Masahiro Murakawa
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Paper Abstract

This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

Paper Details

Date Published: 20 March 2015
PDF: 9 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94141E (20 March 2015); doi: 10.1117/12.2082368
Show Author Affiliations
Hirokazu Nosato, National Institute of Advanced Industrial Science and Technology (Japan)
Hidenori Sakanashi, National Institute of Advanced Industrial Science and Technology (Japan)
Eiichi Takahashi, National Institute of Advanced Industrial Science and Technology (Japan)
Masahiro Murakawa, National Institute of Advanced Industrial Science and Technology (Japan)


Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)

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