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

Akemi Gálvez; Iztok Fister; Iztok Fister; Eneko Osaba; Javier Del Ser; Andrés Iglesias

doi:10.1007/978-3-319-99626-4_31

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

Akemi Gálvez
, Iztok Fister
, Iztok Fister
, Eneko Osaba
, Javier Del Ser
, Andrés Iglesias^*

^*Autor correspondiente de este trabajo

Producción científica: Capítulo del libro/informe/acta de congreso › Capítulo › revisión exhaustiva

9 Citas (Scopus)

Resumen

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.

Idioma original	Inglés
Título de la publicación alojada	Studies in Computational Intelligence
Editorial	Springer Verlag
Páginas	357-368
Número de páginas	12
DOI	https://doi.org/10.1007/978-3-319-99626-4_31
Estado	Publicada - 2018

Serie de la publicación

Nombre	Studies in Computational Intelligence
Volumen	798
ISSN (versión impresa)	1860-949X

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

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 B{\'e}zier 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.",

keywords = "Bat algorithm, Border detection, Computational intelligence, Medical images, Nature-inspired metaheuristic techniques, Skin lesion",

author = "Akemi G{\'a}lvez and Iztok Fister and Iztok Fister and Eneko Osaba and \{Del Ser\}, Javier and Andr{\'e}s Iglesias",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.",

year = "2018",

doi = "10.1007/978-3-319-99626-4\_31",

language = "English",

series = "Studies in Computational Intelligence",

publisher = "Springer Verlag",

pages = "357--368",

booktitle = "Studies in Computational Intelligence",

address = "Germany",

}

Automatic fitting of feature points for border detection of skin lesions in medical images with bat algorithm. / Gálvez, Akemi; Fister, Iztok; Fister, Iztok et al.
Studies in Computational Intelligence. Springer Verlag, 2018. p. 357-368 (Studies in Computational Intelligence; Vol. 798).

Producción científica: Capítulo del libro/informe/acta de congreso › Capítulo › revisión exhaustiva

TY - CHAP

T1 - Automatic fitting of feature points for border detection of skin lesions in medical images with bat algorithm

AU - Gálvez, Akemi

AU - Fister, Iztok

AU - Osaba, Eneko

AU - Del Ser, Javier

AU - Iglesias, Andrés

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Bat algorithm

KW - Border detection

KW - Computational intelligence

KW - Medical images

KW - Nature-inspired metaheuristic techniques

KW - Skin lesion

UR - https://www.scopus.com/pages/publications/85053473678

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T3 - Studies in Computational Intelligence

SP - 357

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BT - Studies in Computational Intelligence

PB - Springer Verlag

ER -

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

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