A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images

Gagan Saini; Rani Oomman Panicker; Biju Soman; Jeny Rajan

doi:10.1109/DISCOVER.2016.7806223

A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images

Gagan Saini
, Rani Oomman Panicker
, Biju Soman
, Jeny Rajan

School of Computer Engineering

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

10 Citations (Scopus)

Abstract

Automatic tuberculosis (TB) detection methods using microscopic images are becoming more popular now a days. Auto-focusing is the first and foremost step in the development of an automated microscope for TB detection. Different focus measures exist for the selection of in-focus image from both fluorescence and bright field microscopic images. Recently, some researchers have investigated and compared several different focus measures for TB sputum microscopy. In this study we focused on bright field microscopic images and considered around 20 popular focus measures. Experiments were conducted on a large set of images having different features.

Original language	English
Title of host publication	2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	95-100
Number of pages	6
ISBN (Electronic)	9781509016235
DOIs	https://doi.org/10.1109/DISCOVER.2016.7806223
Publication status	Published - 2016
Event	2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Mangalore, India Duration: 13-08-2016 → 14-08-2016

Publication series

Name	2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings

Conference

Conference	2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016
Country/Territory	India
City	Mangalore
Period	13-08-16 → 14-08-16

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Electrical and Electronic Engineering
Computer Networks and Communications
Hardware and Architecture

UN SDGs

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

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10.1109/DISCOVER.2016.7806223

Cite this

Saini, G., Panicker, R. O., Soman, B., & Rajan, J. (2016). A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images. In 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings (pp. 95-100). Article 7806223 (2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DISCOVER.2016.7806223

Saini, Gagan ; Panicker, Rani Oomman ; Soman, Biju et al. / A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images. 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 95-100 (2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings).

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title = "A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images",

abstract = "Automatic tuberculosis (TB) detection methods using microscopic images are becoming more popular now a days. Auto-focusing is the first and foremost step in the development of an automated microscope for TB detection. Different focus measures exist for the selection of in-focus image from both fluorescence and bright field microscopic images. Recently, some researchers have investigated and compared several different focus measures for TB sputum microscopy. In this study we focused on bright field microscopic images and considered around 20 popular focus measures. Experiments were conducted on a large set of images having different features.",

author = "Gagan Saini and Panicker, \{Rani Oomman\} and Biju Soman and Jeny Rajan",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 ; Conference date: 13-08-2016 Through 14-08-2016",

year = "2016",

doi = "10.1109/DISCOVER.2016.7806223",

language = "English",

series = "2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings",

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

pages = "95--100",

booktitle = "2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings",

address = "United States",

}

Saini, G, Panicker, RO, Soman, B & Rajan, J 2016, A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images. in 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings., 7806223, 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 95-100, 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016, Mangalore, India, 13-08-16. https://doi.org/10.1109/DISCOVER.2016.7806223

A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images. / Saini, Gagan; Panicker, Rani Oomman; Soman, Biju et al.
2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 95-100 7806223 (2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings).

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

TY - GEN

T1 - A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images

AU - Saini, Gagan

AU - Panicker, Rani Oomman

AU - Soman, Biju

AU - Rajan, Jeny

PY - 2016

Y1 - 2016

N2 - Automatic tuberculosis (TB) detection methods using microscopic images are becoming more popular now a days. Auto-focusing is the first and foremost step in the development of an automated microscope for TB detection. Different focus measures exist for the selection of in-focus image from both fluorescence and bright field microscopic images. Recently, some researchers have investigated and compared several different focus measures for TB sputum microscopy. In this study we focused on bright field microscopic images and considered around 20 popular focus measures. Experiments were conducted on a large set of images having different features.

AB - Automatic tuberculosis (TB) detection methods using microscopic images are becoming more popular now a days. Auto-focusing is the first and foremost step in the development of an automated microscope for TB detection. Different focus measures exist for the selection of in-focus image from both fluorescence and bright field microscopic images. Recently, some researchers have investigated and compared several different focus measures for TB sputum microscopy. In this study we focused on bright field microscopic images and considered around 20 popular focus measures. Experiments were conducted on a large set of images having different features.

UR - https://www.scopus.com/pages/publications/85015873156

UR - https://www.scopus.com/pages/publications/85015873156#tab=citedBy

U2 - 10.1109/DISCOVER.2016.7806223

DO - 10.1109/DISCOVER.2016.7806223

M3 - Conference contribution

AN - SCOPUS:85015873156

T3 - 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings

SP - 95

EP - 100

BT - 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016

Y2 - 13 August 2016 through 14 August 2016

ER -

Saini G, Panicker RO, Soman B, Rajan J. A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images. In 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 95-100. 7806223. (2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings). doi: 10.1109/DISCOVER.2016.7806223

A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images

Abstract

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All Science Journal Classification (ASJC) codes

UN SDGs

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