An efficient approach to sputum image segmentation using improved fuzzy local information C means clustering algorithm for tuberculosis diagnosis

Tuberculosis is one of an infectious threatening disease affected one third of world's population but its fatality rate can controlled by diagnosing and treating at an early stage itself. Ziehl-Neelsen stained sputum smear microscopy is the most popular diagnosis method in developing countries....

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Bibliographic Details

Published in:	2017 International Conference on Inventive Computing and Informatics (ICICI) pp. 126 - 130
Main Authors:	Mithra, K. S., Emmanuel, W. R. Sam
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.11.2017
Subjects:	Clustering algorithms Fast generalized FCM and IFLICM Fuzzy C Means Image segmentation Linear programming Microorganisms Microscopy Robustness Signal processing algorithms Sputum Image tuberculosis
Online Access:	Get full text
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