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Automatic Colorectal Polyp Detection in Colonoscopy Video Frames
Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. His...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
West Asia Organization for Cancer Prevention
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454689/ https://www.ncbi.nlm.nih.gov/pubmed/28030914 http://dx.doi.org/10.22034/APJCP.2016.17.11.4869 |
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author | K, Geetha C, Rajan |
author_facet | K, Geetha C, Rajan |
author_sort | K, Geetha |
collection | PubMed |
description | Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. Histograms of binary patterns computed across regions are used to describe textures. Every pixel is contrasted relative to gray levels of neighbourhood pixels. In this study, colorectal polyp detection was performed with colonoscopy video frames, with classification via J48 and Fuzzy. Features such as color, discrete cosine transform (DCT) and LBP were used in confirming the superiority of the proposed method in colorectal polyp detection. The performance was better than with other current methods. |
format | Online Article Text |
id | pubmed-5454689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | West Asia Organization for Cancer Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-54546892017-08-28 Automatic Colorectal Polyp Detection in Colonoscopy Video Frames K, Geetha C, Rajan Asian Pac J Cancer Prev Research Article Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. Histograms of binary patterns computed across regions are used to describe textures. Every pixel is contrasted relative to gray levels of neighbourhood pixels. In this study, colorectal polyp detection was performed with colonoscopy video frames, with classification via J48 and Fuzzy. Features such as color, discrete cosine transform (DCT) and LBP were used in confirming the superiority of the proposed method in colorectal polyp detection. The performance was better than with other current methods. West Asia Organization for Cancer Prevention 2016 /pmc/articles/PMC5454689/ /pubmed/28030914 http://dx.doi.org/10.22034/APJCP.2016.17.11.4869 Text en Copyright: © Asian Pacific Journal of Cancer Prevention http://creativecommons.org/licenses/BY-SA/4.0 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License |
spellingShingle | Research Article K, Geetha C, Rajan Automatic Colorectal Polyp Detection in Colonoscopy Video Frames |
title | Automatic Colorectal Polyp Detection in Colonoscopy Video Frames |
title_full | Automatic Colorectal Polyp Detection in Colonoscopy Video Frames |
title_fullStr | Automatic Colorectal Polyp Detection in Colonoscopy Video Frames |
title_full_unstemmed | Automatic Colorectal Polyp Detection in Colonoscopy Video Frames |
title_short | Automatic Colorectal Polyp Detection in Colonoscopy Video Frames |
title_sort | automatic colorectal polyp detection in colonoscopy video frames |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454689/ https://www.ncbi.nlm.nih.gov/pubmed/28030914 http://dx.doi.org/10.22034/APJCP.2016.17.11.4869 |
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