Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection

Dawid Połap; Marcin Woźniak; Robertas Damaševičius; Wei Wei

doi:10.1109/SSCI.2018.8628869

Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection

Department of Artificial Intelligence Modelling (RMS/RMS2)

Kaunas University of Technology
Xi'an University of Technology

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

33 Citations (Scopus)

Abstract

Rapid detection of potential threads can speed up medical examination and help to start the treatment without delays. Automatic analysis of x-ray screening is a complex, multi-step process that can be beneficial for more efficient examinations in pulmonary clinics. Traditional methods use image segmentation to cut out interesting areas for further analysis of deviations from the norm (i.e., unhealthy tissues detection). However the area is extracted as a whole part, but for sensitive and more patient oriented examinations we need approach that will be extending segmentation only with necessary elements. In this article we present research results on application of heuristic method for detection over aggregated x-ray image that comes from implemented segmentation.

Original language	English
Title of host publication	Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018
Editors	Suresh Sundaram
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2298-2303
Number of pages	6
ISBN (Electronic)	9781538692769
DOIs	https://doi.org/10.1109/SSCI.2018.8628869
Publication status	Published - 2 Jul 2018
Event	8th IEEE Symposium Series on Computational Intelligence, SSCI 2018 - Bangalore, India Duration: 18 Nov 2018 → 21 Nov 2018

Publication series

Name	Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018

Conference

Conference	8th IEEE Symposium Series on Computational Intelligence, SSCI 2018
Country/Territory	India
City	Bangalore
Period	18/11/18 → 21/11/18

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Heuristic
image detection
image segmentation
key-points
x-ray

ASJC Scopus subject areas

Artificial Intelligence
Theoretical Computer Science

Access to Document

10.1109/SSCI.2018.8628869

Cite this

Połap, D., Woźniak, M., Damaševičius, R., & Wei, W. (2018). Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. In S. Sundaram (Ed.), Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018 (pp. 2298-2303). Article 8628869 (Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2018.8628869

Połap, Dawid ; Woźniak, Marcin ; Damaševičius, Robertas et al. / Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. editor / Suresh Sundaram. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 2298-2303 (Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018).

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title = "Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection",

abstract = "Rapid detection of potential threads can speed up medical examination and help to start the treatment without delays. Automatic analysis of x-ray screening is a complex, multi-step process that can be beneficial for more efficient examinations in pulmonary clinics. Traditional methods use image segmentation to cut out interesting areas for further analysis of deviations from the norm (i.e., unhealthy tissues detection). However the area is extracted as a whole part, but for sensitive and more patient oriented examinations we need approach that will be extending segmentation only with necessary elements. In this article we present research results on application of heuristic method for detection over aggregated x-ray image that comes from implemented segmentation.",

keywords = "Heuristic, image detection, image segmentation, key-points, x-ray",

author = "Dawid Po{\l}ap and Marcin Wo{\'z}niak and Robertas Dama{\v s}evi{\v c}ius and Wei Wei",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th IEEE Symposium Series on Computational Intelligence, SSCI 2018 ; Conference date: 18-11-2018 Through 21-11-2018",

year = "2018",

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doi = "10.1109/SSCI.2018.8628869",

language = "English",

series = "Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018",

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

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Połap, D , Woźniak, M , Damaševičius, R & Wei, W 2018, Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. in S Sundaram (ed.), Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018., 8628869, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018, Institute of Electrical and Electronics Engineers Inc., pp. 2298-2303, 8th IEEE Symposium Series on Computational Intelligence, SSCI 2018, Bangalore, India, 18/11/18. https://doi.org/10.1109/SSCI.2018.8628869

Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. / Połap, Dawid ; Woźniak, Marcin ; Damaševičius, Robertas et al.
Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. ed. / Suresh Sundaram. Institute of Electrical and Electronics Engineers Inc., 2018. p. 2298-2303 8628869 (Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018).

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

TY - GEN

T1 - Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection

AU - Połap, Dawid

AU - Woźniak, Marcin

AU - Damaševičius, Robertas

AU - Wei, Wei

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Rapid detection of potential threads can speed up medical examination and help to start the treatment without delays. Automatic analysis of x-ray screening is a complex, multi-step process that can be beneficial for more efficient examinations in pulmonary clinics. Traditional methods use image segmentation to cut out interesting areas for further analysis of deviations from the norm (i.e., unhealthy tissues detection). However the area is extracted as a whole part, but for sensitive and more patient oriented examinations we need approach that will be extending segmentation only with necessary elements. In this article we present research results on application of heuristic method for detection over aggregated x-ray image that comes from implemented segmentation.

AB - Rapid detection of potential threads can speed up medical examination and help to start the treatment without delays. Automatic analysis of x-ray screening is a complex, multi-step process that can be beneficial for more efficient examinations in pulmonary clinics. Traditional methods use image segmentation to cut out interesting areas for further analysis of deviations from the norm (i.e., unhealthy tissues detection). However the area is extracted as a whole part, but for sensitive and more patient oriented examinations we need approach that will be extending segmentation only with necessary elements. In this article we present research results on application of heuristic method for detection over aggregated x-ray image that comes from implemented segmentation.

KW - Heuristic

KW - image detection

KW - image segmentation

KW - key-points

KW - x-ray

UR - https://www.scopus.com/pages/publications/85062795985

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M3 - Conference contribution

AN - SCOPUS:85062795985

T3 - Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018

SP - 2298

EP - 2303

BT - Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Połap D , Woźniak M , Damaševičius R, Wei W. Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. In Sundaram S, editor, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2298-2303. 8628869. (Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018). doi: 10.1109/SSCI.2018.8628869

Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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