Automatic differentiation of melanoma and clark nevus skin lesions

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 6514, Issue PART 2, 2007, Pages

  LeAnder, R W ^a   Kasture, A ^a   Pandey, A ^a   Umbaugh, S E ^a  

^a SOUTHERN ILLINOIS UNIVERSITY EDWARDSVILLE   (United States)

Author keywords

Classification algorithm; Color normalization; Dermoscopic images; Preprocessing; Quantitative image analysis; Relative color images; Skin cancer; Tumor differentiation; Tumor identification; Tumor texture features

Indexed keywords

AUTOMATION; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE RECOGNITION; OPTIMIZATION; TUMORS;

CLASSIFICATION ALGORITHMS; COLOR NORMALIZATION; DERMOSCOPIC IMAGES; QUANTITATIVE IMAGE ANALYSIS; RELATIVE COLOR IMAGES; SKIN CANCER; TUMOR DIFFERENTIATION; TUMOR IDENTIFICATION; TUMOR TEXTURE FEATURES;

DERMATITIS;

EID: 35248868403     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.709986     Document Type: Conference Paper

References (4)

1. Y. (Iris) Cheng, R. Swamisai, S. Umbaugh, R. Moss, W. V. Stoecker, S. Teegala, S. K. Srinivasan, "Skin lesion classification using relative color features, " Skin Research and Technology (Denmark), Accepted for publication, 2007.
2. I. Cheng, "Skin tumor classification using relative color features," Master thesis, Department of Electrical and Computer Engineering, Southern Illinois University Edwardsville, 2005.
3. S.E. Umbaugh, "Computer Imaging: Digital Image Analysis and Processing," CRC Press, 2005.
4. US 2004 Cancer Facts and Figures, American Cancer Society, American Cancer Society, Inc, 2004.