Automatic Methods for Mycobacterium Detection on Stained Sputum Smear Images: a Survey
| Autor: | W. R. Sam Emmanuel, K. S. Mithra |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
medicine.medical_specialty
020205 medical informatics biology business.industry 02 engineering and technology biology.organism_classification Computer Graphics and Computer-Aided Design Smear microscopy Mycobacterium tuberculosis Tuberculosis diagnosis 0202 electrical engineering electronic engineering information engineering medicine Sputum 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Lung region medicine.symptom Intensive care medicine business Mycobacterium |
| Zdroj: | Pattern Recognition and Image Analysis. 28:310-320 |
| ISSN: | 1555-6212 1054-6618 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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