Automated tuberculosis screening using image processing tools

B. Castaneda, N. G. Aguilar, J. Ticona, D. Kanashiro, R. Lavarello, L. Huaroto

Research output: Contribution to conferencePaper

2 Scopus citations

Abstract

We present a preliminary work as a proof of concept on how image processing algorithms can be applied to detect and diagnose Tuberculosis in microscopic images of sputum samples stained with the Ziehl-Neelsen method. 300 images were acquired at the Hospital Nacional Dos de Mayo and processed using edge detection and mathematical morphology to extract objects of interest. Bacilli are discriminated from these objects applying a classifier based on the Mahalanobis distance and using shape characteristics as features. Results show a specificity value over 90% which is close to previously reported attempts on samples processed with Auramine. © 2010 IEEE.
Original languageAmerican English
Pages111
Number of pages1
DOIs
StatePublished - 9 Jul 2010
Externally publishedYes
EventPan American Health Care Exchanges, PAHCE 2010 -
Duration: 9 Jul 2010 → …

Conference

ConferencePan American Health Care Exchanges, PAHCE 2010
Period9/07/10 → …

Fingerprint Dive into the research topics of 'Automated tuberculosis screening using image processing tools'. Together they form a unique fingerprint.

  • Cite this

    Castaneda, B., Aguilar, N. G., Ticona, J., Kanashiro, D., Lavarello, R., & Huaroto, L. (2010). Automated tuberculosis screening using image processing tools. 111. Paper presented at Pan American Health Care Exchanges, PAHCE 2010, . https://doi.org/10.1109/PAHCE.2010.5474590