Open Access Open Access  Restricted Access Subscription or Fee Access

Survey on Various Techniques Used in Mycobacterium Bacillus Detection from Sputum Images for Tuberculosis Diagnosis

B. Sankaragomathi, K. Swetha


Tuberculosis is a terrible, transferrable disease instigated by infection with Mycobacterium tuberculosis bacillus. A common diagnosis of this infection is the microscopic examination of sputum smears of affected persons. Tuberculosis is a disease with one of the most leading causes of deaths in the world, however, its fatality index could be reduced if it is diagnosed and treated on time. The Ziehl-Neelson stained sputum smear method is most used method for bacilli detection and developing a proper diagnosis by the specialist. Detection of tuberculosis involves different stages such as image preprocessing, segmentation, feature extraction and classification. This paper summarizes the study of various techniques of mycobacterium bacillus detection from sputum images.


Pre-processing, Segmentation, Feature extraction, Classification, Ziehl-Neelson

Full Text:



K.S.Mithra, W.R.Sam Emmanuel, “Automated identifiacation of mycobacterium bacillus from spuctum images for tuberculosis diagnosis” Springer (2019).

Rethabile Khutlang, Sriram Krishnan, Ronald Dendere, Andrew Whitelaw, Konstantinos Veropoulos, Genevieve Learmonth, and Tania S. Douglas, “Classification of Mycobacterium tuberculosis in Images of ZN-Stained Sputum Smears” IEEE transactions on information technology in biomedicine, vol. 14, no. 4(2010).

V. Ayma, R. De Lamare, B. Castaneda, “An Adaptive Filtering Approach for Segmentation of Tuberculosis Bacteria in Ziehl-Neelsen Sputum Stained Images” published in IEEE Latin America Congress on Computational Intelligence (2015)

Lavanya Govindan, Padmasini. N, Mohamed Yacin, “Automated Tuberculosis Screening using Zeihl Neelson Image” IEEE International Conference on Engineering and Technology (ICETECH) (2015)

Selen Ayas, Murat Ekinc, “Random forest-based tuberculosis bacteria classification in images of ZN-stained sputum smear samples” Springer (2014)

Mohammad Imran Shah, Smriti Mishra, Vinod Kumar Yadav, Arun Chauhan, Malay Sarkar, Sudarshan K. Sharma, and Chittaranjan Rout, “Ziehl–Neelsen sputum smear microscopy image database: a resource to facilitate automated bacilli detection for tuberculosis diagnosis” Journal of Medical Imaging Vol 4(2), ( 2017)

Jorge Luis Diaz-Huerta, Adriana del Carmen Tellez-Anguiano, Miguelangel FragaAguilar1, Jose Antonio Gutierrez-Gnecchi1, Sergio Arellano-Caldero, “Image processing for AFB segmentation in bacilloscopies of pulmonary tuberculosis diagnosis” PLoS ONE 14(7), e0218861 (2019)

Eben Godsway Dzodanu, Justice Afrifa, Desmond Omane Acheampong, Issac Dadzie, “Diagnostic Yield of Fluorescence and Ziehl-Neelsen Staining Techniques in the Diagnosis of Pulmonary Tuberculosis: A Comparative Study in a District Health Facility” Hindawi Tuberculosis Research and Treatment , Article ID 4091937 (2019)

R.Khutlang, S.Krishnan, A.Whitelaw & T.S. Douglas, “Automated detection of tuberculosis in Ziehl-Neelsen-stained sputums mearsusing two one-class classifiers” JournalofMicroscopy,Vol.237,Pt12010,pp.96–102 (2019)

Sonaal Kant, Muktabh Mayank Srivastava, “Towards Automated Tuberculosis detection using Deep Learning”IEEE Symposium Series on Computational Intelligence(2018)

Ebenezer Priya, Subramanian Srinivasan, “Automated object and image level classification of TB images using support vector neural network classifier” ELSEVIER,Volume 36,Issue 4(2016)

Rodriguez MZ, Comin CH, Casanova D, Bruno OM, Amancio DR, Costa LdF, “Clustering algorithms: A comparative approach” PLoS ONE 14(1): e0210236(2019)

Riries Rulaningtyas, Andriyan Bayu Suksmono, Tati Mengko, Putri Saptawati, “Multi Patch Approach in K-Means Clustering Method for Color Image Segmentation in Pulmonary Tuberculosis Identification”4th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME)(2015)

Reshma S R, Rehannara Beegum T, “ Microscope image processing for TB diagnosis using shape features and ellipse fitting”IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)(2017)

D. Nithiyapriya, I. Laurence Aroquiaraj, “Performance Analysis of Color Images Using Thresholding Techniques for Image Segmentation in Ziehl- Neelsen Sputum Slide Images” International Journal of Computational Intelligence and Informatics, Vol. 7: No. 4(2018)


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.