Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images

被引：0
|
作者：
Yan, Sineng [1 ]
Liu, Hongying [1 ]
Sun, Li [1 ]
Zhou, Mei [1 ]
Xiao, ZhiRui [1 ]
Zhuang, Quanjie [2 ]
机构：
[1] East China Normal Univ, Shanghai Key Lab Multidimens Informat Proc, Shanghai, Peoples R China
[2] Shanghai Lanche Biol Technol Co Ltd, Shanghai, Peoples R China
来源：
2018 11TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2018) | 2018年
基金：
中国国家自然科学基金;
关键词：
Mycobacterium tuberculosis; image segmentation; image recognition; watershed algorithm;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Tuberculosis is one of the top 10 causes of death worldwide. In order to reduce the workload of doctors and the probability of human error, this paper presents an automatic detection algorithm for Mycobacterium tuberculosis in Ziehl-Neelsen Sputum Smear Images. The algorithm uses color feature and three morphological characters, which are aspect ratio, circularity and area. Background Equalization algorithm is proposed to utilize color feature sufficiently. This algorithm takes advantage of the watershed algorithm and the channel "a" in Lab color space. Experimental results accuracy of the proposed algorithm.
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页数：6
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