Automatic Identification of Mycobacterium tuberculosis in Ziehl-Neelsen Stained Sputum Smear Microscopy Images using a Two-stage Classifier

Lucas de Assis Soares, Klaus Fabian Coco, Evandro Ottoni Teatini Salles, Saulo Bortolon

Abstract

This paper presents a method for the automatic identification of Mycobacterium tuberculosis in Ziehl-Neelsen stained sputum smear microscopy images, the most common bacilloscopy method in developing countries due to its low costs. The proposed method is divided in two stages: a projection of the original coloured image followed by the segmentation and the elimination of large and small segmented structures, and the classification of structures using neural networks and support vector machines. The segmentation of structures presents a loss of bacilli of 1.31 %, while the elimination of areas increases the loss to 14.39 %. The evaluation of the classification of structures is made using cross validation and a maximum sensitivity of 94.25 % is obtained. The presented method has a low computational cost, allying performance and efficiency.

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Paper Citation


in Harvard Style

Soares L., Coco K., Salles E. and Bortolon S. (2015). Automatic Identification of Mycobacterium tuberculosis in Ziehl-Neelsen Stained Sputum Smear Microscopy Images using a Two-stage Classifier . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 186-191. DOI: 10.5220/0005345201860191


in Bibtex Style

@conference{visapp15,
author={Lucas de Assis Soares and Klaus Fabian Coco and Evandro Ottoni Teatini Salles and Saulo Bortolon},
title={Automatic Identification of Mycobacterium tuberculosis in Ziehl-Neelsen Stained Sputum Smear Microscopy Images using a Two-stage Classifier},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={186-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005345201860191},
isbn={978-989-758-091-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Automatic Identification of Mycobacterium tuberculosis in Ziehl-Neelsen Stained Sputum Smear Microscopy Images using a Two-stage Classifier
SN - 978-989-758-091-8
AU - Soares L.
AU - Coco K.
AU - Salles E.
AU - Bortolon S.
PY - 2015
SP - 186
EP - 191
DO - 10.5220/0005345201860191