@article{0b0edc56ccf5468398f239c0c198203b,
title = "Identification of tuberculosis bacteria based on shape and color",
abstract = "Tuberculosis and other mycobacteriosis are serious illnesses which control is based on early diagnosis. A technique commonly used consists of analyzing sputum images for detecting bacilli. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid high errors. Image-processing techniques provide a good tool for improving the manual screening of samples. In this paper, a new autofocus algorithm and a new bacilli detection technique is presented with the aim to attain a high specificity rate and reduce the time consumed to analyze such sputum samples. This technique is based on the combined use of some invariant shape features together with a simple thresholding operation on the chromatic channels. Some feature descriptors have been extracted from bacilli shape using an edited dataset of samples. A k-means clustering technique was applied for classification purposes and the sensitivity vs specificity results were evaluated using a standard ROC analysis procedure. {\textcopyright} 2004 Elsevier Ltd. All rights reserved.",
author = "Forero, {Manuel G.} and Filip Sroubek and Gabriel Crist{\'o}bal",
year = "2004",
month = aug,
day = "1",
doi = "10.1016/j.rti.2004.05.007",
language = "American English",
pages = "251--262",
journal = "Real-Time Imaging",
issn = "1077-2014",
publisher = "Academic Press Inc.",
}
