Image classification of microscopic colonic images using textural properties and KSOM
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 e...
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| Main Authors: | , , , |
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| Format: | text |
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Animo Repository
2010
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2813 |
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| Institution: | De La Salle University |
| Summary: | 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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