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Discontinuity, Nonlinearity, and Complexity

Dimitry Volchenkov (editor), Dumitru Baleanu (editor)

Dimitry Volchenkov(editor)

Mathematics & Statistics, Texas Tech University, 1108 Memorial Circle, Lubbock, TX 79409, USA

Email: dr.volchenkov@gmail.com

Dumitru Baleanu (editor)

Cankaya University, Ankara, Turkey; Institute of Space Sciences, Magurele-Bucharest, Romania

Email: dumitru.baleanu@gmail.com


Ant Colony Optimization Algorithm for Lesion Border Detection in Dermoscopic Images

Discontinuity, Nonlinearity, and Complexity 7(4) (2018) 429--436 | DOI:10.5890/DNC.2018.12.007

Asmae Ennaji, Abdellah Aarab

LESSI laboratory, Faculty of Sciences Dhar el Mahraz, Fes, USMBA, Morocco

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Abstract

Medical image segmentation plays a crucial role in computer aided diagnosis system that have a significant potential for early detection of skin cancer. The aim of segmentation process in this field is to facilitate the characterization and the visualization of the lesion in dermoscopic images. This paper proposes a new method for improving the lesion border detection in dermoscopic images, based on the ant colony optimization algorithm. Our experiments show that the proposed method achieved a significant improvement in image segmentation when compared to the deterministic canny procedure.

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