Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images

Sineng Yan; Hongying Liu; Li Sun; Mei Zhou; Zhirui Xiao; Quanjie Zhuang

doi:10.1109/CISP-BMEI.2018.8633191

Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images

Sineng Yan
, Hongying Liu
, Li Sun
, Mei Zhou
, Zhirui Xiao
, Quanjie Zhuang

School of Communication and Electronic Engineering

East China Normal University
Ltd.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

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 confirmed the high accuracy of the proposed algorithm.

Original language	English
Title of host publication	Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
Editors	Wei Li, Qingli Li, Lipo Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538676042
DOIs	https://doi.org/10.1109/CISP-BMEI.2018.8633191
State	Published - 2 Jul 2018
Event	11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 - Beijing, China Duration: 13 Oct 2018 → 15 Oct 2018

Publication series

Name	Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018

Conference

Conference	11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
Country/Territory	China
City	Beijing
Period	13/10/18 → 15/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Mycobacterium tuberculosis
image recognition
image segmentation
watershed algorithm

Access to Document

10.1109/CISP-BMEI.2018.8633191

Cite this

Yan, S., Liu, H., Sun, L., Zhou, M., Xiao, Z., & Zhuang, Q. (2018). Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images. In W. Li, Q. Li, & L. Wang (Eds.), Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 Article 8633191 (Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISP-BMEI.2018.8633191

Yan, Sineng ; Liu, Hongying ; Sun, Li et al. / Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images. Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. editor / Wei Li ; Qingli Li ; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2018. (Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018).

@inproceedings{047f3cd552f64f98a9f6dcb8f92959cd,

title = "Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images",

abstract = "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 confirmed the high accuracy of the proposed algorithm.",

keywords = "Mycobacterium tuberculosis, image recognition, image segmentation, watershed algorithm",

author = "Sineng Yan and Hongying Liu and Li Sun and Mei Zhou and Zhirui Xiao and Quanjie Zhuang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 ; Conference date: 13-10-2018 Through 15-10-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/CISP-BMEI.2018.8633191",

language = "英语",

series = "Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Wei Li and Qingli Li and Lipo Wang",

booktitle = "Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018",

address = "美国",

}

Yan, S, Liu, H, Sun, L , Zhou, M, Xiao, Z & Zhuang, Q 2018, Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images. in W Li, Q Li & L Wang (eds), Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018., 8633191, Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018, Institute of Electrical and Electronics Engineers Inc., 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018, Beijing, China, 13/10/18. https://doi.org/10.1109/CISP-BMEI.2018.8633191

Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images. / Yan, Sineng; Liu, Hongying; Sun, Li et al.
Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. ed. / Wei Li; Qingli Li; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2018. 8633191 (Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images

AU - Yan, Sineng

AU - Liu, Hongying

AU - Sun, Li

AU - Zhou, Mei

AU - Xiao, Zhirui

AU - Zhuang, Quanjie

PY - 2018/7/2

Y1 - 2018/7/2

N2 - 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 confirmed the high accuracy of the proposed algorithm.

AB - 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 confirmed the high accuracy of the proposed algorithm.

KW - Mycobacterium tuberculosis

KW - image recognition

KW - image segmentation

KW - watershed algorithm

UR - https://www.scopus.com/pages/publications/85062884631

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DO - 10.1109/CISP-BMEI.2018.8633191

M3 - 会议稿件

AN - SCOPUS:85062884631

T3 - Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018

BT - Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018

A2 - Li, Wei

A2 - Li, Qingli

A2 - Wang, Lipo

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018

Y2 - 13 October 2018 through 15 October 2018

ER -

Yan S, Liu H, Sun L , Zhou M, Xiao Z, Zhuang Q. Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images. In Li W, Li Q, Wang L, editors, Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8633191. (Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018). doi: 10.1109/CISP-BMEI.2018.8633191

Detection of Mycobacterium Tuberculosis in Ziehl-Neelsen Sputum Smear Images

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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