Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images

Vishnu Makkapati; Ravindra Agrawal; Raviraja Acharya

doi:10.1109/COASE.2009.5234173

Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images

Vishnu Makkapati, Ravindra Agrawal, Raviraja Acharya

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

61 Citations (Scopus)

Abstract

Quality of tuberculosis (TB) diagnosis by manual observation varies depending on the quality of the smear and skill of the pathologist. To overcome this problem, a method for diagnosis of TB from ZN-stained sputum smear images is presented in this paper. Hue color component based approach is proposed to segment the bacilli by adaptive choice of the hue range. The bacilli are declared to be valid or invalid depending on the presence of beaded structure inside them. The beaded structure is segmented by thresholding the saturation component of the bacilli pixels. Clumps of bacilli and other artifacts are removed by thresholding the area, thread length and thread width parameters of the bacilli. Results presented for several images taken from different patients show that the scheme detects the presence of TB accurately.

Original language	English
Title of host publication	2009 IEEE International Conference on Automation Science and Engineering, CASE 2009
Pages	217-220
Number of pages	4
DOIs	https://doi.org/10.1109/COASE.2009.5234173
Publication status	Published - 12-11-2009
Event	2009 IEEE International Conference on Automation Science and Engineering, CASE 2009 - Bangalore, India Duration: 22-08-2009 → 25-08-2009

Conference

Conference	2009 IEEE International Conference on Automation Science and Engineering, CASE 2009
Country/Territory	India
City	Bangalore
Period	22-08-09 → 25-08-09

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Software

UN SDGs

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

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10.1109/COASE.2009.5234173

Cite this

@inproceedings{98709b28ef4448a1a337bd292c6f6301,

title = "Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images",

abstract = "Quality of tuberculosis (TB) diagnosis by manual observation varies depending on the quality of the smear and skill of the pathologist. To overcome this problem, a method for diagnosis of TB from ZN-stained sputum smear images is presented in this paper. Hue color component based approach is proposed to segment the bacilli by adaptive choice of the hue range. The bacilli are declared to be valid or invalid depending on the presence of beaded structure inside them. The beaded structure is segmented by thresholding the saturation component of the bacilli pixels. Clumps of bacilli and other artifacts are removed by thresholding the area, thread length and thread width parameters of the bacilli. Results presented for several images taken from different patients show that the scheme detects the presence of TB accurately.",

author = "Vishnu Makkapati and Ravindra Agrawal and Raviraja Acharya",

year = "2009",

month = nov,

day = "12",

doi = "10.1109/COASE.2009.5234173",

language = "English",

isbn = "9781424445783",

pages = "217--220",

booktitle = "2009 IEEE International Conference on Automation Science and Engineering, CASE 2009",

note = "2009 IEEE International Conference on Automation Science and Engineering, CASE 2009 ; Conference date: 22-08-2009 Through 25-08-2009",

}

Makkapati, V, Agrawal, R & Acharya, R 2009, Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images. in 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009., 5234173, pp. 217-220, 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009, Bangalore, India, 22-08-09. https://doi.org/10.1109/COASE.2009.5234173

TY - GEN

T1 - Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images

AU - Makkapati, Vishnu

AU - Agrawal, Ravindra

AU - Acharya, Raviraja

PY - 2009/11/12

Y1 - 2009/11/12

N2 - Quality of tuberculosis (TB) diagnosis by manual observation varies depending on the quality of the smear and skill of the pathologist. To overcome this problem, a method for diagnosis of TB from ZN-stained sputum smear images is presented in this paper. Hue color component based approach is proposed to segment the bacilli by adaptive choice of the hue range. The bacilli are declared to be valid or invalid depending on the presence of beaded structure inside them. The beaded structure is segmented by thresholding the saturation component of the bacilli pixels. Clumps of bacilli and other artifacts are removed by thresholding the area, thread length and thread width parameters of the bacilli. Results presented for several images taken from different patients show that the scheme detects the presence of TB accurately.

AB - Quality of tuberculosis (TB) diagnosis by manual observation varies depending on the quality of the smear and skill of the pathologist. To overcome this problem, a method for diagnosis of TB from ZN-stained sputum smear images is presented in this paper. Hue color component based approach is proposed to segment the bacilli by adaptive choice of the hue range. The bacilli are declared to be valid or invalid depending on the presence of beaded structure inside them. The beaded structure is segmented by thresholding the saturation component of the bacilli pixels. Clumps of bacilli and other artifacts are removed by thresholding the area, thread length and thread width parameters of the bacilli. Results presented for several images taken from different patients show that the scheme detects the presence of TB accurately.

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U2 - 10.1109/COASE.2009.5234173

DO - 10.1109/COASE.2009.5234173

M3 - Conference contribution

AN - SCOPUS:70449103206

SN - 9781424445783

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EP - 220

BT - 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009

T2 - 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009

Y2 - 22 August 2009 through 25 August 2009

ER -

Segmentation and classification of tuberculosis bacilli from zn-stained sputum smear images

Abstract

Conference

All Science Journal Classification (ASJC) codes

UN SDGs

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