13 November 2001 Automatic sputum color image segmentation for tuberculosis diagnosis
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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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manuel G. Forero-Vargas, Manuel G. Forero-Vargas, Eduard L. Sierra-Ballen, Eduard L. Sierra-Ballen, Josue Alvarez-Borrego, Josue Alvarez-Borrego, Jose Luis Pech-Pacheco, Jose Luis Pech-Pacheco, Gabriel Cristobal-Perez, Gabriel Cristobal-Perez, Luis Alcala, Luis Alcala, Manuel Desco, Manuel Desco, "Automatic sputum color image segmentation for tuberculosis diagnosis", Proc. SPIE 4471, Algorithms and Systems for Optical Information Processing V, (13 November 2001); doi: 10.1117/12.449343; https://doi.org/10.1117/12.449343
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