RT Conference Proceedings
T1 Computing rational border curves of melanoma and other skin lesions from medical images with bat algorithm
A1 Gálvez, Akemi
A1 Fister, Iztok
A1 Fister, Iztok
A1 Del Ser, Javier
A1 Osaba, Eneko
A1 Iglesias, Andrés
AB Border detection of melanoma and other skin lesions from images is an important step in the medical image processing pipeline. Although this task is typically carried out manually by the dermatologists, some recent papers have applied evolutionary computation techniques to automate this process. However, these works are only focused on the polynomial case, ignoring the more powerful (but also more difficult) case of rational curves. In this paper, we address this problem with rational Bézier curves by applying the bat algorithm, a popular bio-inspired swarm intelligence technique for optimization. Experimental results on two examples of medical images of melanomas show that this method is promising, as it outperforms the polynomial approach and can be applied to medical images without further pre/post-processing.
PB Association for Computing Machinery, Inc
SN 9781450367486
YR 2019
FD 2019-07-13
LK https://hdl.handle.net/11556/1899
UL https://hdl.handle.net/11556/1899
LA eng
NO Gálvez , A , Fister , I , Fister , I , Del Ser , J , Osaba , E & Iglesias , A 2019 , Computing rational border curves of melanoma and other skin lesions from medical images with bat algorithm . in GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion . GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion , Association for Computing Machinery, Inc , pp. 1675-1682 , 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 , Prague , Czech Republic , 13/07/19 . https://doi.org/10.1145/3319619.3326873
NO conference
NO Publisher Copyright: © 2019 Association for Computing Machinery.
NO A. Galvez and A. Iglesias acknowledge the financial support from the project PDE-GIR of the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 778035, and the project TIN2017-89275-R of the Agencia Estatal de In-vestigación, Spanish Ministry of Science, Innovation and Universities (Computer Science National Program) and European Funds EFRD (AEI/FEDER, UE). I. Fister Jr. thanks the financial support from the Slovenian Research Agency (Research Core Founding No. P2-0057). E. Osaba and J. Del Ser would like to thank the Basque Government for its funding support through the EMAITEK program. I. Fister acknowledges the financial support from the Slovenian Research Agency (Research Core Founding No. P2-0041). A. Galvez and A. Iglesias acknowledge the financial support from the project PDE-GIR of the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 778035, and the project TIN2017-89275-R of the Agencia Estatal de In-vestigación, Spanish Ministry of Science, Innovation and Universities (Computer Science National Program) and European Funds EFRD (AEI/FEDER, UE). I. Fister Jr. thanks the financial support from the Slovenian Research Agency (Research Core Founding No. P2-0057). E. Osaba and J. Del Ser would like to thank the Basque Government for its funding support through the EMAITEK program. I. Fister acknowledges the financial support from the Slovenian Research Agency (Research Core Founding No. P2-0041).
DS TECNALIA Publications
RD 28 jul 2024