title: Automated identification of tubercle bacilli in sputum. A preliminary investigation.
abstract: OBJECTIVE
  To use an automated method to detect tubercle bacilli in sputum specimens.
  
  
  METHODS
  Using fluorescence microscopy, tubercle bacilli were identified on auramine-stained sputum specimens. Images were then captured with a digital camera and enhanced through imaging processing techniques. The bacilli were recognized using neural network classifiers.
  
  
  RESULTS
  This preliminary investigation demonstrated a sensitivity of 94.1% for the identification of individual bacilli. As there are usually fairly numerous tubercle bacilli in the sputum of patients with active pulmonary tuberculosis, the overall diagnostic accuracy of sputum smear-positive patients can be expected to be very high.
  
  
  CONCLUSIONS
  Potential benefits of automated screening for TB bacilli are: rapid, accurate, inexpensive diagnosis; the ability to screen larger numbers of people; increased resources to monitor patients; and reduction in health risks to staff.
authors.affiliation: Advanced Computing Research Center, University of Bristol, United Kingdom. veropoul@cs.bris.ac.uk
authors.forename: K
authors.initials: K
authors.lastname: Veropoulos
authors.forename: G
authors.initials: G
authors.lastname: Learmonth
authors.forename: C
authors.initials: C
authors.lastname: Campbell
authors.forename: B
authors.initials: B
authors.lastname: Knight
authors.forename: J
authors.initials: J
authors.lastname: Simpson
mesh_terms: D005069:Evaluation Studies as Topic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence; D009169:Mycobacterium tuberculosis / Q000166:cytology*; D016571:Neural Networks, Computer; D012680:Sensitivity and Specificity; D013183:Sputum / Q000382:microbiology*; D014397:Tuberculosis, Pulmonary / Q000175:diagnosis*