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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Automated detection of tuberculosis in Ziehl-Neelsen-stained sputum smears using two one-class classifiers
Journal of Microscopy, Volume 237, No. 1, Year 2010
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Description
Screening for tuberculosis in high-prevalence countries relies on sputum smear microscopy. We present a method for the automated identification of Mycobacterium tuberculosis in images of Ziehl-Neelsen-stained sputum smears obtained using a bright-field microscope. We use two stages of classification. The first comprises a one-class pixel classifier for object segmentation. Geometric transformation invariant features are extracted for implementation of the second stage, namely one-class object classification. Different classifiers are compared; the sensitivity of all tested classifiers is above 90% for the identification of a single bacillus object using all extracted features. The mixture of Gaussians classifier performed well in both stages of classification. This method may be used as a step in the automation of tuberculosis screening, in order to reduce technician involvement in the process. © 2009 The Royal Microscopical Society.
Authors & Co-Authors
Khutlang, Rethabile
South Africa, Cape Town
Mrc/uct Medical Imaging Research Unit
Krishnan, Sriram
South Africa, Cape Town
Mrc/uct Medical Imaging Research Unit
Whitelaw, Andrew C.
South Africa, Cape Town
University of Cape Town
Douglas, Tania S.
South Africa, Cape Town
Mrc/uct Medical Imaging Research Unit
Statistics
Citations: 51
Authors: 4
Affiliations: 2
Identifiers
Doi:
10.1111/j.1365-2818.2009.03308.x
e-ISSN:
13652818
Study Design
Cross Sectional Study