Image classification of microscopic colonic images using textural properties and KSOM
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Article
Source Title
International Journal of Biomedical Engineering and Technology
Volume
3
Issue
3-4
First Page
308
Last Page
318
Publication Date
1-1-2010
Abstract
Colorectal cancer is considered the third most common neoplasm in the world. Traditionally, pathologists use a microscope to examine histopathological images of biopsy samples taken from patients and make judgments based on their professional expertise. Since this procedure is performed by a human expert, it is therefore subject to inconsistencies due to factors that might affect human performance. To overcome this problem, this paper proposes the use of Kohonen self-organising map and Haralick texture in the analysis of microscopic colonic images. The results presented here are preliminary and show great promise. Copyright © 2010 Inderscience Enterprises Ltd.
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Digitial Object Identifier (DOI)
10.1504/IJBET.2010.032698
Recommended Citation
Gan Lim, L. A., Naguib, R. G., Dadios, E. P., & Avila, J. C. (2010). Image classification of microscopic colonic images using textural properties and KSOM. International Journal of Biomedical Engineering and Technology, 3 (3-4), 308-318. https://doi.org/10.1504/IJBET.2010.032698
Disciplines
Computer Sciences | Medicine and Health Sciences
Keywords
Colon (Anatomy)—Cancer—Imaging; Self-organizing maps; Diagnostic imaging
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