19 March 2015 Anisotropic tubular filtering for automatic detection of acid-fast bacilli in Ziehl-Neelsen stained sputum smear samples
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Abstract
One of the main factors for high workload in pulmonary pathology in developing countries is the relatively large proportion of tuberculosis (TB) cases which can be detected with high throughput using automated approaches. TB is caused by Mycobacterium tuberculosis, which appears as thin, rod-shaped acid-fast bacillus (AFB) in Ziehl-Neelsen (ZN) stained sputum smear samples. In this paper, we present an algorithm for automatic detection of AFB in digitized images of ZN stained sputum smear samples under a light microscope. A key component of the proposed algorithm is the enhancement of raw input image using a novel anisotropic tubular filter (ATF) which suppresses the background noise while simultaneously enhancing strong anisotropic features of AFBs present in the image. The resulting image is then segmented using color features and candidate AFBs are identified. Finally, a support vector machine classifier using morphological features from candidate AFBs decides whether a given image is AFB positive or not. We demonstrate the effectiveness of the proposed ATF method with two different feature sets by showing that the proposed image analysis pipeline results in higher accuracy and F1-score than the same pipeline with standard median filtering for image enhancement.
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Shan-e-Ahmed Raza, Shan-e-Ahmed Raza, M. Qaisar Marjan, M. Qaisar Marjan, Muhammad Arif, Muhammad Arif, Farhana Butt, Farhana Butt, Faisal Sultan, Faisal Sultan, Nasir M. Rajpoot, Nasir M. Rajpoot, } "Anisotropic tubular filtering for automatic detection of acid-fast bacilli in Ziehl-Neelsen stained sputum smear samples", Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 942005 (19 March 2015); doi: 10.1117/12.2081835; https://doi.org/10.1117/12.2081835
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