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Classification of Oral Submucous Fibrosis using SVM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 78 - Number 3 |
| Year of Publication: 2013 |
| Authors: S. Venkatakrishnan, V. Ramalingam, S. Palanivel |
10.5120/13467-9311
|
S. Venkatakrishnan, V. Ramalingam, S. Palanivel . Classification of Oral Submucous Fibrosis using SVM. International Journal of Computer Applications. 78, 3 ( September 2013), 8-11. DOI=10.5120/13467-9311
Abstract
Medical images form an essential source of information for various important tasks such as diagnosis of diseases, surgical planning, medical reference, research and training. Oral submucous fibrosis [OSMF] is a chronic debilitating disease of the oral cavity characterized by inflammation and progressive fibrosis of the submucosal tissues. Support Vector Machine [SVM] is a statistic machine learning technique that has been successfully applied in the pattern recognition and is based on the principle of structural risk minimization. In this paper a histogram based feature extraction technique has been proposed to classify normal images and OSMF affected images using SVM. An attempt is made to provide an enhanced knowledge about computer aided diagnosis of this potentially malignant disorder, to health care providers in order to help in differentiating the OSMF affected tissue from normal. Experiments showed significantly satisfactory results with an accuracy of 94%.
References
- Van der Waal. I,Potentially malignant disorders of the oral and oropharyngeal mucosa;present concepts of management,Oral Oncology,46(6):423-5,June 2010.
- Kunio Doi. Computer-aided diagnosis in medical imaging:historical review, current status and future potential. Journal-Computerised medical imaging and Graphics, 31:198-211, 2007.
- M. M. R. Krishnan, . R. Acharya,C. Chakraborty, A. K. Ray, Automated Diagnosis of Oral Cancer Using Higher Order Spectra Features and Local Binary Pattern: A Comparative Study TCRT , 10(5):391-504,October 2011.
- Shah. P. Sch. of Med. Sci. & Technol. , IIT,- Kharagpur, Kharagpur, India ; Krishnan, M. M. R. Chakraborty, C, Ray, A. K. , Morphometric Pattern Analysis of Basal Cell Nuclei for Oral Cancer Screening, Bioinformatics and Biomedical Engineering [iCBBE] 2010 National conference, 1-4, June 2010.
- Ray AA Krishnan. MM. Shah. P, Choudhary AA. Chakraborty. C. Paul RR. Textural characterization ofhistopathological images for oral sub-mucous fibrosisdetection. Tissue cell, 43(5):318–30, October 2011.
- Anirban Mukherjee Jyotirmoy Chatterjee Ranjan. R. Paul Pranab. K. Dutta, M. E. Tathagata Ray, D. Shivashanker Reddy. Detection of constituent layers of histological oral sub-mucous fibrosis images using the hybrid segmentation algorithm. Oral Oncology, 44(12):1167–1171,December 2008.
- M. Muthuramakrishnan,Pal,Suneel. K. Bomminayuni,Chandan Chakraborthy, Automated classification of cells in sub-epithelial connective tissue of oral sub-mucous fibrosis-An SVM based approach. Computers in Biology and medicine,39(12):1096-1104. December 2009.
- Chandan . K. Ray M. MuthuRamaKrishnan,PratikShah. Statistical analysis of textural features for improved classification of oral histopathological images. Journal of Medical Systems, 36(2):865–881, April 2012.
- Chandan Chakraborty Ajoy. K. Ray Ranjan. R. PaulM. MuthuRamaKrishnan, Anirudh Choudhry. Texturebased segmentation of epithelial layer from oral histological images. Micron, 42(6):632–641, August 2011.
- U. Rajendra Acharya, Mousumi Pal, Ranjan Rashmi Paul, LimChoo Min Ajay kumar Ray Jyotirmoy Chatterjee Chandan Chakraborty M. Muthuramakrishnan, Vikram Venkatraghavan. Automated oral cancer identification using histopathological images: A hybrid feature extractionparadigm. 43(2-3):352–364, February 2012.
- Pratik Shah M. Tech. Chandan Chakraborty- MuthuRama Krishnan Mookiah,s Ajoy K. Ray. Brownian motion curvebased textural classification and its application in cancer diagnosis. Analytical and Quantitative Cytology and Histology,, May 2013.
- MuthuramaKrishnan. M. Shah. P, Structural markers for normal oral mucosa and oral sub-mucous fibrosis. Micron, 41(4):312–20, June 2010.
- Anirban Mukherjee,Ranjan Rashmi Paul,Keya Chaudhuri,Jyotirmoy Chatterjee,Mousumi Paul,Provas Banerjeee,kanchan Mukherjee,Swapna, Performance analysis of different wavelet feature vectors in quantification of oral precancerous condition, Oral Oncology,42(9):914-28,October 2006.
- Jsyotirmoy Chatterjee Rusha Patra, Chandan Chakraborty. Textural analysis of spinous layer for grading oral submucousfibrosis ,. International Journal of Computer Applications, 47:975-8887,June 2012.
- R R Paul, A Mukherjee, P K Dutta, S. Banerjee, M Pal, J Chatterjee, K. Chaudhuri, K. Mukkerjee,A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition, J. Clin Pathol,58(2):932-938,February 2005.
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