Research on Detection of Mycobacterium Tuberculosis from Microscopic Sputum Smear Images using Image Segmentation

被引:0
|
作者
Saravanan, D. [1 ]
Bhavya, R. [1 ]
Archanaa, G. I. [1 ]
Karthika, D. [1 ]
Subban, Ravi [2 ]
机构
[1] IFET Coll Engn & Technol, Dept Comp Sci & Engn, Villupuram, India
[2] Pondicherry Univ, Sch Engn & Technol, Dept Comp Sci, Pondicherry, India
关键词
color space; image segmentation; classification models; DIAGNOSIS; ANTIGENS; BACTERIA;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Tuberculosis (TB) is a deadly disease caused by a bacteria called Mycobacterium tuberculosis that can affect lungs mostly. Besides it is a disease that affects not only lungs in the body of a human being but other parts also. There are few diseases that kills the human population. The commonly used tools that can detect TB are: GeneXpert, microscopy, tuberculin bacilli test (TST), chest X-ray, interferon-y release assay (IGRA), and culture test. But the sputum smear microscopy is the mostly used tool. The merits of using this tool are: it is supposed to be easier, faster and cheaper than other methods without requiring much technical expertise and yielding sufficiently fast results. But the problem with this tool is that the screening may fail to detect TB and requires some eye strain with concentration. The automatic screening method will remove this problem. This paper provides research review on TB detection using image processing techniques.
引用
收藏
页码:969 / 974
页数:6
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