Automated diagnosis of skin cancer using digital image processing and mixture-of-experts

Biomedizinische Technik

Volumn 46, Issue s1, 2001, Pages 376-377

  Kreutz, Martin ^a,b   Anschütz, Maik ^a,b   Grünendick, Thorsten ^a,b   Rick, Andreas ^a,b   Gehlen, Stefan ^a,b   Hoffmann, Klaus ^c  

^a VISIOmedd AG   (Germany)

^b ZN Vision Technologies AG   (Germany)

^c ST JOSEF HOSPITAL   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 80052034901     PISSN: 00135585     EISSN: None     Source Type: Journal    
DOI: 10.1515/bmte.2001.46.s1.376     Document Type: Article

References (10)

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4. H. Handels et al. Feature selection for optimized skin tumor recognition using G As. Artif Intell Med, 16:283-297,1999.
5. R. Husemann et al. Computerised diagnosis of skin cancer using neural networks. In P. Altmeyer et al., editors, Skin Cancer and UV Radiation, pages 1052-1063. Springer, 1997.
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7. M. Kreutz et al. Automated diagnosis of skin cancer using digital image processing and mixture-of-experts. In H. Handels et al., editors, Bildverarbeitung für die Medizin-Algorithmen, Systeme, Anwendungen, Informatik aktuell, pages 357-361, Berlin, 2001. Springer.
8. G. Pott et al. Danaos-Automated skin cancer diagnosis with neural networks. In Aw 7th EADV, 1998.
9. W. V. Stoccker et al. Texture in skin lesions: Comparison of three methods to determine smoothness. Computerized Medical Imaging and Graphics, 16:179 190,1992.
10. W. Stolz ct. al. Improvement of monitoring of melanocytie skin lesions with the use of a computarized acquisition and surveillance unit with a skin surface microscopic television camera. J Am Acad Dermatol 35, 1996.