Indonesian Journal of Tropical and Infectious Disease
Vol 3, No 1 (2012)

USING LEARNING VECTOR QUANTIZATION METHOD FOR AUTOMATED IDENTIFICATION OF MYCOBACTERIUM TUBERCULOSIS

Purwanti, Endah ( Department of Physics Science & Technology Faculty Airlangga University, Surabaya, Indonesia )
Widiyanti, Prihartini ( Institute of Tropical Disease Airlangga University, Surabaya, Indonesia )



Article Info

Publish Date
06 Jul 2015

Abstract

In this paper, we are developing an automated method for the detection of tubercle bacilli in clinical specimens, principally the sputum. This investigation is the first attempt to automatically identify TB bacilli in sputum using image processing and learning vector quantization (LVQ) techniques. The evaluation of the learning vector quantization (LVQ) was carried out on Tuberculosis dataset show that average of accuracy is 91,33%.

Copyrights © 2012






Journal Info

Abbrev

IJTID

Publisher

Subject

Earth & Planetary Sciences Health Professions Medicine & Pharmacology Public Health

Description

This journal is a peer-reviewed journal established to promote the recognition of emerging and reemerging diseases specifically in Indonesia, South East Asia, other tropical countries and around the world, and to improve the understanding of factors involved in disease emergence, prevention, and ...