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Proceedings Paper

Automatic sputum color image segmentation for tuberculosis diagnosis
Author(s): Manuel G. Forero-Vargas; Eduard L. Sierra-Ballen; Josue Alvarez-Borrego; Jose Luis Pech-Pacheco; Gabriel Cristobal-Perez; Luis Alcala; Manuel Desco
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Paper Abstract

Tuberculosis (TB) and other mycobacteriosis are serious illnesses which control is mainly based on presumptive diagnosis. Besides of clinical suspicion, the diagnosis of mycobacteriosis must be done through genus specific smears of clinical specimens. However, these techniques lack of sensitivity and consequently clinicians must wait culture results as much as two months. Computer analysis of digital images from these smears could improve sensitivity of the test and, moreover, decrease workload of the micobacteriologist. Bacteria segmentation of particular species entails a complex process. Bacteria shape is not enough as a discriminant feature, because there are many species that share the same shape. Therefore the segmentation procedure requires to be improved using the color image information. In this paper we present two segmentation procedures based on fuzzy rules and phase-only correlation techniques respectively that will provide the basis of a future automatic particle' screening.

Paper Details

Date Published: 13 November 2001
PDF: 11 pages
Proc. SPIE 4471, Algorithms and Systems for Optical Information Processing V, (13 November 2001);
Show Author Affiliations
Manuel G. Forero-Vargas, Univ. Nacional de Colombia (Colombia)
Eduard L. Sierra-Ballen, Univ. Nacional de Colombia (Colombia)
Josue Alvarez-Borrego, CICESE (United States)
Jose Luis Pech-Pacheco, Consejo Superior de Investigaciones Cientificas (Spain)
Gabriel Cristobal-Perez, Consejo Superior de Investigaciones Cientificas (Spain)
Luis Alcala, Hospital General Gregorio Maranon (Spain)
Manuel Desco, Hospital General Gregorio Maranon (Spain)

Published in SPIE Proceedings Vol. 4471:
Algorithms and Systems for Optical Information Processing V
Bahram Javidi; Demetri Psaltis, Editor(s)

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