Automated systems for microscopic and radiographic tuberculosis screening

Abstract

Abstract: China has the world's second largest tuberculosis epidemic(after India) with very high TB infection,TB incident,drug resistance,and mortality rate. Rapid,accurate diagnosis is critical for timely initiation of treatment and ultimately control of the disease. WHO-recommended smear fluorescent microscopy is the most common diagnostic tools in the laboratories to detect acid fast bacilli(AFB) after staining with Auramine-O. Routine visual slide screening for identification and counting of AFB is a tedious,labor-intensive task. Low quality,inconsistent slide staining technique,debris,variation in human perception,and fatigue lead to sensitivity as low as 40%, especially in scanty specimens. Applying an automatic microscopy system using artificial intelligence based computer aided diagnostic(CAD) technologies to the automated diagnosis of TB presents the opportunity to address the shortcomings of current techniques in diagnosing TB from sputum smears. For the identification of TB suspects in low-resource settings,WHO has recommended chest X-ray (CXR) screening as a very efficient triage referral test. A challenge in those regions,however,is the imbalance in the affected population and available radiology services. In addressing this need, application of CAD using artificial intelligence into a low-cost automated tool for pulmonary TB (PTB) in CXR images can directly close this gap.

Key words: Pulmonary tuberculosis, Automated microscopy, Digital radiography, Computer aided diagnosis, Artificial intelligence

Fleming Y.M.Lure, Stefan Jaeger, Sameer Antani. Automated systems for microscopic and radiographic tuberculosis screening[J]. Electronic Journal of Emerging Infectious Diseases, 2017, 2(1): 5-9.

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