ROI Extraction in Thermographic Breast Images Using Genetic Algorithms

L. C. Mendes; E. O. Rodrigues; S. C. Izidoro; A. Conci; P. Liatsis

doi:10.1109/IWSSIP48289.2020.9145346

ROI Extraction in Thermographic Breast Images Using Genetic Algorithms

L. C. Mendes
, E. O. Rodrigues
, S. C. Izidoro
, A. Conci
, P. Liatsis

Electrical Engineering

Universidade Federal de Itajuba
Universidade Tecnológica Federal do Paraná
Universidade Federal Fluminense

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

5 Scopus citations

Abstract

This work proposes the use of Genetic Algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color information, a fitness function based on cardioids, and GA. This is the first work in the literature to propose a Region of Interest (ROI) extraction based on GA and cariods. ROI extraction can improve the accuracy of cancer detection and assist with the standardization of acquisition protocols. The method is able to successfully separate the breast region in 52 out of 58 images, while being fully automatic, and not requiring manual selection of seed points.

Original language	British English
Title of host publication	Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020
Editors	Anselmo C. Paiva, Aura Conci, Geraldo Braz, Joao Dallyson S. Almeida, Leandro A. F. Fernandes
Publisher	IEEE Computer Society
Pages	111-115
Number of pages	5
ISBN (Electronic)	9781728175393
DOIs	https://doi.org/10.1109/IWSSIP48289.2020.9145346
State	Published - Jul 2020
Event	27th International Conference on Systems, Signals and Image Processing, IWSSIP 2020 - Niteroi, Brazil Duration: 1 Jul 2020 → 3 Jul 2020

Publication series

Name	International Conference on Systems, Signals, and Image Processing
Volume	2020-July
ISSN (Print)	2157-8672
ISSN (Electronic)	2157-8702

Conference

Conference	27th International Conference on Systems, Signals and Image Processing, IWSSIP 2020
Country/Territory	Brazil
City	Niteroi
Period	1/07/20 → 3/07/20

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Evolutionary Algorithms
Genetic Algorithms
Image Segmentation
Infrared Images
Region of Interest
Thermography

Access to Document

10.1109/IWSSIP48289.2020.9145346

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Mendes, L. C., Rodrigues, E. O., Izidoro, S. C., Conci, A., & Liatsis, P. (2020). ROI Extraction in Thermographic Breast Images Using Genetic Algorithms. In A. C. Paiva, A. Conci, G. Braz, J. D. S. Almeida, & L. A. F. Fernandes (Eds.), Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020 (pp. 111-115). Article 9145346 (International Conference on Systems, Signals, and Image Processing; Vol. 2020-July). IEEE Computer Society. https://doi.org/10.1109/IWSSIP48289.2020.9145346

Mendes, L. C. ; Rodrigues, E. O. ; Izidoro, S. C. et al. / ROI Extraction in Thermographic Breast Images Using Genetic Algorithms. Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020. editor / Anselmo C. Paiva ; Aura Conci ; Geraldo Braz ; Joao Dallyson S. Almeida ; Leandro A. F. Fernandes. IEEE Computer Society, 2020. pp. 111-115 (International Conference on Systems, Signals, and Image Processing).

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title = "ROI Extraction in Thermographic Breast Images Using Genetic Algorithms",

abstract = "This work proposes the use of Genetic Algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color information, a fitness function based on cardioids, and GA. This is the first work in the literature to propose a Region of Interest (ROI) extraction based on GA and cariods. ROI extraction can improve the accuracy of cancer detection and assist with the standardization of acquisition protocols. The method is able to successfully separate the breast region in 52 out of 58 images, while being fully automatic, and not requiring manual selection of seed points.",

keywords = "Evolutionary Algorithms, Genetic Algorithms, Image Segmentation, Infrared Images, Region of Interest, Thermography",

author = "Mendes, \{L. C.\} and Rodrigues, \{E. O.\} and Izidoro, \{S. C.\} and A. Conci and P. Liatsis",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 27th International Conference on Systems, Signals and Image Processing, IWSSIP 2020 ; Conference date: 01-07-2020 Through 03-07-2020",

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doi = "10.1109/IWSSIP48289.2020.9145346",

language = "British English",

series = "International Conference on Systems, Signals, and Image Processing",

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Mendes, LC, Rodrigues, EO, Izidoro, SC, Conci, A & Liatsis, P 2020, ROI Extraction in Thermographic Breast Images Using Genetic Algorithms. in AC Paiva, A Conci, G Braz, JDS Almeida & LAF Fernandes (eds), Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020., 9145346, International Conference on Systems, Signals, and Image Processing, vol. 2020-July, IEEE Computer Society, pp. 111-115, 27th International Conference on Systems, Signals and Image Processing, IWSSIP 2020, Niteroi, Brazil, 1/07/20. https://doi.org/10.1109/IWSSIP48289.2020.9145346

ROI Extraction in Thermographic Breast Images Using Genetic Algorithms. / Mendes, L. C.; Rodrigues, E. O.; Izidoro, S. C. et al.
Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020. ed. / Anselmo C. Paiva; Aura Conci; Geraldo Braz; Joao Dallyson S. Almeida; Leandro A. F. Fernandes. IEEE Computer Society, 2020. p. 111-115 9145346 (International Conference on Systems, Signals, and Image Processing; Vol. 2020-July).

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

TY - GEN

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AU - Rodrigues, E. O.

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N2 - This work proposes the use of Genetic Algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color information, a fitness function based on cardioids, and GA. This is the first work in the literature to propose a Region of Interest (ROI) extraction based on GA and cariods. ROI extraction can improve the accuracy of cancer detection and assist with the standardization of acquisition protocols. The method is able to successfully separate the breast region in 52 out of 58 images, while being fully automatic, and not requiring manual selection of seed points.

AB - This work proposes the use of Genetic Algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color information, a fitness function based on cardioids, and GA. This is the first work in the literature to propose a Region of Interest (ROI) extraction based on GA and cariods. ROI extraction can improve the accuracy of cancer detection and assist with the standardization of acquisition protocols. The method is able to successfully separate the breast region in 52 out of 58 images, while being fully automatic, and not requiring manual selection of seed points.

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KW - Image Segmentation

KW - Infrared Images

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ER -

Mendes LC, Rodrigues EO, Izidoro SC, Conci A, Liatsis P. ROI Extraction in Thermographic Breast Images Using Genetic Algorithms. In Paiva AC, Conci A, Braz G, Almeida JDS, Fernandes LAF, editors, Proceedings of the 2020 International Conference on Systems, Signals and Image Processing, IWSSIP 2020. IEEE Computer Society. 2020. p. 111-115. 9145346. (International Conference on Systems, Signals, and Image Processing). doi: 10.1109/IWSSIP48289.2020.9145346

ROI Extraction in Thermographic Breast Images Using Genetic Algorithms

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

OpenUrl availability

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