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Automatic Methods for Mycobacterium Detection on Stained Sputum Smear Images: a Survey

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Abstract

Mycobacterium tuberculosis (MTB) is one of the leading causes of adult morbidity and mortality worldwide, especially in developing countries like India. MTB is caused by the mycobacterium bacillus which mainly generates infections on lung region but sometimes affects other parts also. Sputum smear microscopy is the widely used tool for MTB diagnosis in most of the developing countries since it is less costly. Manual detection of bacilli from stained sputum images are time consuming since it may take 15 minutes per slide for detection, reducing number of slides which affects the accuracy of the output. Thus computer aided automatic methods provide obviously an optimum solution in disease diagnosis within less time and without highly experienced laboratory experts. There are so many papers published for automatic tuberculosis diagnosis from microscopic sputum images so far. This paper provides a survey of those published papers from the year 2002 to 2016. Thus it provides an overview of available methods and its accuracy and hence it will be useful for researchers and practitioners working in the field of automation of sputum smear microscopy.

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Authors and Affiliations

  1. Research Scholar, Department of Computer Science, Nesamony Memorial Christian College, Manonmaniam Sundaranar University, Abishekappatti, Tirunelveli, Tamil Nadu, India

    K. S. Mithra

  2. Department of Computer Science, Nesamony Memorial Christian College, Marthandam, Tamil Nadu, India

    W. R. Sam Emmanuel

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  1. K. S. Mithra
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Correspondence to K. S. Mithra.

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K. S. Mithra received her M. Phil (Computer Science) degree in 2010 and M.C.A degree in 2009 from Manonmaniam Sundaranar University, Tirunelveli. She was with St.Johns College of arts and science as assistant professor. Now she is doing doctoral research under Manonmaniam Sundaranar University, Tirunelveli. Her interested research areas are steganography, medical imaging and image segmentation.

W. R. Sam Emmanuel received his doctoral degree in computer science in 2012 from Vinayaka Missions University, Salem. He received his M. Phil (Computer Science) degree in 2002 from Manonmaniam Sundaranar University, Tirunelveli and MCA from Bharathidhason University, Tiruchirappalli. He is working as Associate Professor at Nesamony Memorial Christian College, Marthandam. His major research interests are Cryptography, Network Security, Segmentation and Classification.

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Mithra, K.S., Sam Emmanuel, W.R. Automatic Methods for Mycobacterium Detection on Stained Sputum Smear Images: a Survey. Pattern Recognit. Image Anal. 28, 310–320 (2018). https://doi.org/10.1134/S105466181802013X

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