Work place: Dept.of Electronics & Communication Engineering SJB Institute of Technology,Visvesvaraya Technological University, Bangalore,India
Research Interests: Engineering, Computational Engineering, Computational Science and Engineering
Vani V obtained her B.E degree in Electronics & Communication Engineering at Dayananda Sagar College of Engineering; M.Tech in VLSI Design and Embedded Systems from UTL Technologies,VTU. Presently she is working as an Assistant Professor in Dept. of Electronics & Communication Engineering, Sapthagiri College of Engineering, Bangalore. She is also pursuing research under the guidance of Dr.K.V.Mahendra Prashanth in the Dept. of Electronics & Communication Engineering, SJB Institute of Technology, Kengeri, Bengaluru.
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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