Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation

Arti Tiwari; Kamanasish Bhattacharjee; Millie Pant; Jana Nowakova; Vaclav Snasel

doi:10.1007/978-3-030-84910-8_27

Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation

Arti Tiwari, Kamanasish Bhattacharjee, Millie Pant, Jana Nowakova, Vaclav Snasel

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

1 Scopus citations

Abstract

In the pre-processing of the digital thermograms, multi-level thresholding plays a crucial role in the segmentation of thermographic images for better clinical decision support. This paper attempts to optimize the multi-level thresholding method for thermographic image segmentation using Differential Evolution (DE) with the Otsu’s between class variance. We have compared the results of the proposed method with the other popular metaheuristics- PSO, GWO and WOA. We have applied the Wilcoxon rank-sum test for the performance evaluation.

Original language	English
Title of host publication	Advances in Intelligent Networking and Collaborative Systems - The 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS-2021
Editors	Leonard Barolli, Hsing-Chung Chen, Tomoya Enokido
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	253-263
Number of pages	11
ISBN (Print)	9783030849092
DOIs	https://doi.org/10.1007/978-3-030-84910-8_27
State	Published - 1 Jan 2022
Externally published	Yes
Event	13th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2021 - Taichung, Taiwan, Province of China Duration: 1 Sep 2021 → 3 Sep 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	312
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	13th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2021
Country/Territory	Taiwan, Province of China
City	Taichung
Period	1/09/21 → 3/09/21

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-3-030-84910-8_27

Cite this

Tiwari, A., Bhattacharjee, K., Pant, M., Nowakova, J., & Snasel, V. (2022). Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation. In L. Barolli, H.-C. Chen, & T. Enokido (Eds.), Advances in Intelligent Networking and Collaborative Systems - The 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS-2021 (pp. 253-263). (Lecture Notes in Networks and Systems; Vol. 312). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-84910-8_27

Tiwari, Arti ; Bhattacharjee, Kamanasish ; Pant, Millie et al. / Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation. Advances in Intelligent Networking and Collaborative Systems - The 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS-2021. editor / Leonard Barolli ; Hsing-Chung Chen ; Tomoya Enokido. Springer Science and Business Media Deutschland GmbH, 2022. pp. 253-263 (Lecture Notes in Networks and Systems).

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abstract = "In the pre-processing of the digital thermograms, multi-level thresholding plays a crucial role in the segmentation of thermographic images for better clinical decision support. This paper attempts to optimize the multi-level thresholding method for thermographic image segmentation using Differential Evolution (DE) with the Otsu{\textquoteright}s between class variance. We have compared the results of the proposed method with the other popular metaheuristics- PSO, GWO and WOA. We have applied the Wilcoxon rank-sum test for the performance evaluation.",

author = "Arti Tiwari and Kamanasish Bhattacharjee and Millie Pant and Jana Nowakova and Vaclav Snasel",

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Tiwari, A, Bhattacharjee, K, Pant, M, Nowakova, J & Snasel, V 2022, Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation. in L Barolli, H-C Chen & T Enokido (eds), Advances in Intelligent Networking and Collaborative Systems - The 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS-2021. Lecture Notes in Networks and Systems, vol. 312, Springer Science and Business Media Deutschland GmbH, pp. 253-263, 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2021, Taichung, Taiwan, Province of China, 1/09/21. https://doi.org/10.1007/978-3-030-84910-8_27

Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation. / Tiwari, Arti; Bhattacharjee, Kamanasish; Pant, Millie et al.
Advances in Intelligent Networking and Collaborative Systems - The 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS-2021. ed. / Leonard Barolli; Hsing-Chung Chen; Tomoya Enokido. Springer Science and Business Media Deutschland GmbH, 2022. p. 253-263 (Lecture Notes in Networks and Systems; Vol. 312).

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

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AB - In the pre-processing of the digital thermograms, multi-level thresholding plays a crucial role in the segmentation of thermographic images for better clinical decision support. This paper attempts to optimize the multi-level thresholding method for thermographic image segmentation using Differential Evolution (DE) with the Otsu’s between class variance. We have compared the results of the proposed method with the other popular metaheuristics- PSO, GWO and WOA. We have applied the Wilcoxon rank-sum test for the performance evaluation.

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Tiwari A, Bhattacharjee K, Pant M, Nowakova J, Snasel V. Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation. In Barolli L, Chen HC, Enokido T, editors, Advances in Intelligent Networking and Collaborative Systems - The 13th International Conference on Intelligent Networking and Collaborative Systems, INCoS-2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 253-263. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-84910-8_27

Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation

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