Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images

Vishnu Makkapati, Ravindra Agrawal, Raviraja Acharya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

53 Citations (Scopus)

Abstract

Quality of tuberculosis (TB) diagnosis by manual observation varies depending on the quality of the smear and skill of the pathologist. To overcome this problem, a method for diagnosis of TB from ZN-stained sputum smear images is presented in this paper. Hue color component based approach is proposed to segment the bacilli by adaptive choice of the hue range. The bacilli are declared to be valid or invalid depending on the presence of beaded structure inside them. The beaded structure is segmented by thresholding the saturation component of the bacilli pixels. Clumps of bacilli and other artifacts are removed by thresholding the area, thread length and thread width parameters of the bacilli. Results presented for several images taken from different patients show that the scheme detects the presence of TB accurately.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Automation Science and Engineering, CASE 2009
Pages217-220
Number of pages4
DOIs
Publication statusPublished - 12-11-2009
Event2009 IEEE International Conference on Automation Science and Engineering, CASE 2009 - Bangalore, India
Duration: 22-08-200925-08-2009

Conference

Conference2009 IEEE International Conference on Automation Science and Engineering, CASE 2009
CountryIndia
CityBangalore
Period22-08-0925-08-09

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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    Makkapati, V., Agrawal, R., & Acharya, R. (2009). Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images. In 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009 (pp. 217-220). [5234173] https://doi.org/10.1109/COASE.2009.5234173