Automatic Detection of Skin Cancer: Current Status, Path for the Future
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.
W. V. Stoecker et al., "Automatic Detection of Skin Cancer: Current Status, Path for the Future," Proceedings of the 8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 (2013, Barcelona, Spain), vol. 1, pp. 504-508, Institute for Systems and Technologies of Information, Control and Communication (INSTICC), Feb 2013.
8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 (2013: Feb 21-24, Barcelona, Spain)
Electrical and Computer Engineering
Keywords and Phrases
Automatic Detection; Clinical information; Color processing; Dermoscopy; Digital technologies; Melanoma; Research communities; Skin cancers; Computer vision; Data fusion; Diagnosis; Image analysis; Oncology; Stars; Dermatology; Machine vision
Article - Conference proceedings
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