Skin cancer recognition by computer vision

Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier...

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Veröffentlicht in:Computerized medical imaging and graphics 1989, Vol.13 (1), p.31-36
Hauptverfasser: Moss, Randy H., Stoecker, William V., Lin, Shi-Jen, Muruganandhan, Sundararajun, Chu, Kuang-Fu, Poneleit, Kathy M., Mitchell, Carl D.
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Sprache:eng
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Zusammenfassung:Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier transform of the image, the Sun-Wee texture analysis algorithm, and several other image analysis techniques suitable for skin photographs. This image analysis software is designed for use with AI/DERM, an expert system that models diagnosis of skin tumors by dermatologists.
ISSN:0895-6111
1879-0771
DOI:10.1016/0895-6111(89)90076-1