Automated identification of tubercle bacilli in sputum. A preliminary investigation.
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.
Veropoulos
K
K
Advanced Computing Research Center, University of Bristol, United Kingdom. veropoul@cs.bris.ac.uk
Learmonth
G
G
Campbell
C
C
Knight
B
B
Simpson
J
J
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*