An adaptive filtering approach for segmentation of tuberculosis bacteria in Ziehl-Neelsen sputum stained images

V. Ayma, R. De Lamare, B. Castañeda

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

12 Citas (Scopus)

Resumen

Tuberculosis is a disease with one of the most leading causes of deaths in the world, however, its fatality index could be reduced if it is diagnosed and treated on time. The Ziehl-Neelsen stained sputum smear method is the most used for bacilli detection and for developing a proper diagnosis by the specialist. Nevertheless, these stained images do not always present an adequate contrast, then, the elaboration of a reliable diagnosis is a complex, time consuming and a difficult process. This research proposes an alternative method to perform automatic bacilli segmentation in Ziehl-Neelsen images using Adaptive Signal Processing techniques, like the Least Mean Squares and Reduced Rank with Eigendecomposition algorithms. The quantitative results achieved, in correlation and true positives detection, are encouraging and suggest the use of this approach as a feasible alternative, when compared with the classical segmentation techniques, for automatic bacilli segmentation in the Ziehl-Neelsen images.

Idioma originalInglés
Título de la publicación alojada2015 Latin-America Congress on Computational Intelligence, LA-CCI 2015
EditoresMarley M. B. R. Vellasco, Yvan J. Tupac Valdivia, Heitor Silverio Lopes
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781467384186
DOI
EstadoPublicada - 17 mar. 2016
Evento2nd Latin-America Congress on Computational Intelligence, LA-CCI 2015 - Curitiba, Brasil
Duración: 13 oct. 201516 oct. 2015

Serie de la publicación

Nombre2015 Latin-America Congress on Computational Intelligence, LA-CCI 2015

Conferencia

Conferencia2nd Latin-America Congress on Computational Intelligence, LA-CCI 2015
País/TerritorioBrasil
CiudadCuritiba
Período13/10/1516/10/15

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