Work place: Dept.of Electronics & Communication Engineering
Research Interests: Engineering, Medical Informatics, Computational Engineering
Dr.K.V.MahendraPrashanth obtained his B.E. degree in Electronics & Communication Engineering at National Institute of Engineering, Mysore; M.E. degree in Power Electronics from UVCE Bangalore. He received his Ph.D. degree in Electronics & Communication Engineering from VTU. His area of interests are signal processing, active noise control, BioMedical engineering. He has around 24 years of teaching experience. Presently he is working as Professor in Department of Electronics & Communication Engineering, Chief Coordinator for R&D and PG programmes at SJBIT, Bangalore. He has published papers in international and National journals, and presented papers in International conferences. Patent to couple of his innovative work is in progress. At present he is guiding 3 Research Scholars. Received several awards at the State & National level for the projects being guided by Dr Prashanth. Two technical papers authored by Dr. K V M Prashanth were being adjudged as the top two papers; as per the survey report issued by BIOMED publications. He is a Reviewer for international & National Journals. He is the Member of IEEE, Acoustical society of India, ISTE, IEI, and IIAV.
DOI: https://doi.org/10.5815/ijigsp.2017.06.06, Pub. Date: 8 Jun. 2017
Wireless Capsule Endoscopy (WCE) is one of the methods for examination of gastrointestinal (GI) disorders such as obscure GI bleeding, Crohns disease, polyps etc. WCE has been recognized as a less expensive and painless procedure for the diagnosis of GI tract. This paper examines the various image classifiers designed and developed for the purpose of endoscopy focusing specifically on WCE. It is revealed that designing a suitable image classifier is an important prerequisite for accurate and precise diagnosis of malignancy in WCE. The assessment on various image classifiers used for the diagnosis of pathologies in different parts of GI tract shows that classifiers have reduced the diagnosis time for medical experts and also provided reasonably accurate diagnosis of malignancy. However, correlating classifiers and related pathologies is still observed to be challenging. In view of the fact that early detection may decrease the mortality rate significantly, inclination towards computer aided diagnosis are expected to increase in future. There is a need for advanced research in the development of a robust computer aided diagnosis system, capable of diagnosis of various pathologies in GI tract with higher degree of accuracy and reliability. Further, the study depicts that a direct comparison of results of classifier such as accuracy, prediction, sensitivity, specificity and precision to evaluate its performance is challenging due to diversity of image databases. More research is needed to identify and reduce the uncertainties in the application of image classifier to improve the diagnosis accuracy.[...] Read more.
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