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Authors: William V. Stoecker 1 ; Nabin Mishra 2 ; Robert LeAnder 3 ; Ryan K. Rader 4 and R. Joe Stanley 2

Affiliations: 1 Missouri University of Science And Technology, Stoecker & Associates and University of Missouri School of Medicine, United States ; 2 Missouri University of Science And Technology, United States ; 3 Southern Illinois University Edwardsville, United States ; 4 Stoecker & Associates and University of Missouri School of Medicine, United States

Keyword(s): Machine Vision, Melanoma, Image Analysis, Color Processing, Dermoscopy, Skin Cancer.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Early and Biologically-Inspired Vision ; Features Extraction ; Image and Video Analysis ; Medical Image Applications ; Segmentation and Grouping

Abstract: How far are we away from a Star-Trek-like device that can analyze a lesion and assess its malignancy? We review the main challenges in this field in light of the Blois paradigm of clinical judgment and computers. The research community has failed to adequately address several challenges ripe for the application of digital technology: 1) early detection of changing lesions, 2) detection of non-melanoma skin cancers, and 3) detection of benign melanoma mimics. We highlight a new device and recent image analysis advances in abnormal color and texture detection. Anthropomorphic paradigms can be applied to machine vision. Data fusion has the potential to move automatic diagnosis of skin lesions closer to clinical practice. The fusion of Blois’ high-level clinical information with low-level image data can yield high sensitivity and specificity. Synergy between detection devices and humans can get us closer to this Star-Trek-like device.

CC BY-NC-ND 4.0

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Paper citation in several formats:
V. Stoecker, W.; Mishra, N.; LeAnder, R.; K. Rader, R. and Stanley, R. (2013). Automatic Detection of Skin Cancer - Current Status, Path for the Future. In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1; ISSN 2184-4321, pages 504-508. DOI: 10.5220/0004348605040508

@conference{visapp13,
author={William {V. Stoecker}. and Nabin Mishra. and Robert LeAnder. and Ryan {K. Rader}. and R. Joe Stanley.},
title={Automatic Detection of Skin Cancer - Current Status, Path for the Future},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={504-508},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004348605040508},
isbn={978-989-8565-47-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Automatic Detection of Skin Cancer - Current Status, Path for the Future
SN - 978-989-8565-47-1
IS - 2184-4321
AU - V. Stoecker, W.
AU - Mishra, N.
AU - LeAnder, R.
AU - K. Rader, R.
AU - Stanley, R.
PY - 2013
SP - 504
EP - 508
DO - 10.5220/0004348605040508