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

Katedra Modelowania Sztucznej Inteligencji (RMS/RMS2)

Kaunas University of Technology
Xi'an University of Technology

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

33 Cytowania z bazy Scopus

Abstrakt

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.

Język oryginału	angielski
Tytuł publikacji goszczącej	Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018
Redaktorzy	Suresh Sundaram
Wydawca	Institute of Electrical and Electronics Engineers Inc.
Strony	2298-2303
Liczba stron	6
ISBN (elektroniczny)	9781538692769
Identyfikatory DOI	https://doi.org/10.1109/SSCI.2018.8628869
Status publikacji	Opublikowano - 2 lip 2018
Wydarzenie	8th IEEE Symposium Series on Computational Intelligence, SSCI 2018 - Bangalore, Indie Czas trwania: 18 lis 2018 → 21 lis 2018

Seria publikacji

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

Konferencja

Konferencja	8th IEEE Symposium Series on Computational Intelligence, SSCI 2018
Kraj/Terytorium	Indie
Miejscowość	Bangalore
Okres	18/11/18 → 21/11/18

Cele SDG ONZ

Ten wynik przyczynia się do realizacji następujących celów zrównoważonego rozwoju

Cel 3 Dobre zdrowie i dobre samopoczucie

Obszary tematyczne ASJC Scopus

Sztuczna inteligencja
Informatyka teoretyczna

Uzyskaj dostęp do dokumentu

10.1109/SSCI.2018.8628869

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Połap, D., Woźniak, M., Damaševičius, R., & Wei, W. (2018). Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. W S. Sundaram (Red.), Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018 (str. 2298-2303). Artykułu 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 i in. / 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. redaktor / Suresh Sundaram. Institute of Electrical and Electronics Engineers Inc., 2018. str. 2298-2303 (Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018).

@inproceedings{be67c450d031411ca5d51e684cc0d926,

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",

month = jul,

day = "2",

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.",

pages = "2298--2303",

editor = "Suresh Sundaram",

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

address = "United States",

}

Połap, D , Woźniak, M , Damaševičius, R & Wei, W 2018, Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. w S Sundaram (red.), 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., str. 2298-2303, 8th IEEE Symposium Series on Computational Intelligence, SSCI 2018, Bangalore, Indie, 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 i in.
Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. red. / Suresh Sundaram. Institute of Electrical and Electronics Engineers Inc., 2018. str. 2298-2303 8628869 (Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

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

U2 - 10.1109/SSCI.2018.8628869

DO - 10.1109/SSCI.2018.8628869

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

A2 - Sundaram, Suresh

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th IEEE Symposium Series on Computational Intelligence, SSCI 2018

Y2 - 18 November 2018 through 21 November 2018

ER -

Połap D , Woźniak M , Damaševičius R, Wei W. Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection. W Sundaram S, redaktor, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Institute of Electrical and Electronics Engineers Inc. 2018. str. 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

Abstrakt

Seria publikacji

Konferencja

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

Uzyskaj dostęp do dokumentu

Inne pliki i linki

Fingerprint

Cytowanie