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Recent Computer Aided Diagnosis System for Colon Disease Detection
Details
The most common type of colon disease is Colon Cancer, which produces almost a million cases/annum. The doctors can tell the condition of the colon of a patient by watching and examining his/ her colonoscopy video, and the method is used worldwide for checking the various diseases of colon i.e. Colon Polyps, Colorectal Cancer, Ulcerative Colitis, Crohn's Diseases, Gastric Ulcer, bleeding in Colon, Sigmoidal Colon etc. This colorectal cancer strikes about 200,000 people per year, but it can be curable if detected in early stage. Research has demonstrated that early detection and treatment of colorectal diseases can improve treatment outcomes and survival rates during Optical Colonoscopy. These dangerous colorectal diseases are the cause of colorectal cancer although the diagnosis of colonoscopy has been attracting more attention in recent years; this technique is heavily dependent on the practitioner's subject experience. Different practitioners may give inconsistent diagnosis results for the same patient. Therefore, it is very needful to develop computerized colonoscopy video analysis techniques to standardize and objectify this diagnosis method.
Autorentext
I am Mainak Biswas, working as Assistant Professor in The Department of Electrical Engineering at Techno India College of Technology, India. I received M.E. and B.Tech in 2014 and 2012 respectively. My Ph.D. work domain is medical image processing. My subjects of interest are Image Processing, Machine Learning.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786133991231
- Genre Electrical Engineering
- Sprache Englisch
- Anzahl Seiten 80
- Herausgeber LAP LAMBERT Academic Publishing
- Größe H220mm x B150mm x T5mm
- Jahr 2017
- EAN 9786133991231
- Format Kartonierter Einband
- ISBN 6133991232
- Veröffentlichung 21.12.2017
- Titel Recent Computer Aided Diagnosis System for Colon Disease Detection
- Autor Mainak Biswas
- Untertitel Recent Computer Aided Diagnosis System for Colon Disease Detection
- Gewicht 137g