Automatic fitting of feature points for border detection of skin lesions in medical images with bat algorithm

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URI: https://hdl.handle.net/11556/2176
ISSN: 1860-949X
DOI: 10.1007/978-3-319-99626-4_31
Publication date
2018
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Springer Verlag
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Abstract
This paper addresses the problem of automatic fitting of feature points for border detection of skin lesions. This problem is an important task in segmentation of dermoscopy images for semi-automatic early diagnosis of melanoma and other skin lesions. Given a set of feature points selected by a dermatologist, we apply a powerful nature-inspired metaheuristic optimization method called bat algorithm to obtain the free-form parametric Bézier curve that fits the points better in the least-squares sense. Our experimental results on two examples of skin lesions show that the method performs quite well and might be applied to automatic fitting of feature points for border detection in medical images.
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Publisher Copyright: © 2018, Springer Nature Switzerland AG.
Keywords
Bat algorithm , Border detection , Computational intelligence , Medical images , Nature-inspired metaheuristic techniques , Skin lesion , Artificial Intelligence , SDG 3 - Good Health and Well-being
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book part
Citation
Gálvez , A , Fister , I , Fister , I , Osaba , E , Del Ser , J & Iglesias , A 2018 , Automatic fitting of feature points for border detection of skin lesions in medical images with bat algorithm . in Studies in Computational Intelligence . Studies in Computational Intelligence , vol. 798 , Springer Verlag , pp. 357-368 . https://doi.org/10.1007/978-3-319-99626-4_31