Automatic Skin Lesion Segmentation based on Saliency and Color

Giuliana Ramella

2020

Abstract

Segmenting skin lesions in dermoscopic images is a key step for the automatic diagnosis of melanoma. In this framework, this paper presents a new algorithm that after a pre-processing phase aimed at reducing the computation burden, removing artifacts and improving contrast, selects the skin lesion pixels in terms of their saliency and color. The method is tested on a publicly available dataset and is evaluated both qualitatively and quantitatively.

Paper Citation

in Harvard Style

Ramella G. (2020). Automatic Skin Lesion Segmentation based on Saliency and Color. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 452-459. DOI: 10.5220/0009144904520459

in Bibtex Style

@conference{visapp20,
author={Giuliana Ramella},
title={Automatic Skin Lesion Segmentation based on Saliency and Color},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={452-459},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009144904520459},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Automatic Skin Lesion Segmentation based on Saliency and Color
SN - 978-989-758-402-2
AU - Ramella G.
PY - 2020
SP - 452
EP - 459
DO - 10.5220/0009144904520459
PB - SciTePress