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Authors: Michal Haindl and Pavel Žid

Affiliation: The Institute of Information Theory and Automation, Czech Academy of Sciences, Pod Vodárenskou věží 4, Prague, Czech Republic

Keyword(s): Skin Cancer Recognition, Melanoma Detection, Circular Markov Random Field Model.

Abstract: Early and reliable melanoma detection is one of today's significant challenges for dermatologists to allow successful cancer treatment. This paper introduces multispectral rotationally invariant textural features of the Markovian type applied to effective skin cancerous lesions classification. Presented texture features are inferred from the descriptive multispectral circular wide-sense Markov model. Unlike the alternative texture-based recognition methods, mainly using different discriminative textural descriptions, our textural representation is fully descriptive multispectral and rotationally invariant. The presented method achieves high accuracy for skin lesion categorization. We tested our classifier on the open-source dermoscopic ISIC database, containing 23 901 benign or malignant lesions images, where the classifier outperformed several deep neural network alternatives while using smaller training data.

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Paper citation in several formats:
Haindl, M. and Žid, P. (2022). Melanoma Recognition. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 722-729. DOI: 10.5220/0010936400003124

@conference{visapp22,
author={Michal Haindl. and Pavel Žid.},
title={Melanoma Recognition},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={722-729},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010936400003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Melanoma Recognition
SN - 978-989-758-555-5
IS - 2184-4321
AU - Haindl, M.
AU - Žid, P.
PY - 2022
SP - 722
EP - 729
DO - 10.5220/0010936400003124
PB - SciTePress

- Science and Technology Publications, Lda.
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