Skin lesion classification using relative color features

Skin Research and Technology

Volumn 14, Issue 1, 2008, Pages 53-64

  Cheng, Yue ^a   Swamisai, Ragavendar ^a   Umbaugh, Scott E ^a   Moss, Randy H ^b   Stoecker, William V ^c   Teegala, Saritha ^a   Srinivasan, Subhashini K ^a  

^a SOUTHERN ILLINOIS UNIVERSITY EDWARDSVILLE   (United States)

^b Architectural and Environmental Engineering   (United States)

^c Stoecker and Associates   (United States)

Author keywords

CVIP tools; Image classification; Melanoma; Pattern recognition; Relative color features; Skin lesion

Indexed keywords

ALGORITHMS; COLOR; COLOR IMAGE PROCESSING; IMAGE CLASSIFICATION; MATHEMATICAL MODELS; PATTERN RECOGNITION; STATISTICAL METHODS;

MELANOMA; RELATIVE COLOR FEATURES; SKIN LESION;

SKIN;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER PROGRAM; CONTROLLED STUDY; DIFFERENTIAL DIAGNOSIS; DIGITAL IMAGING; DISEASE CLASSIFICATION; DYSPLASTIC NEVUS; ENTROPY; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MEDICAL PHOTOGRAPHY; MELANOMA; NEVUS; PERCEPTRON; SKIN COLOR; SKIN DEFECT; TUMOR DIFFERENTIATION;

ALGORITHMS; COLORIMETRY; DIAGNOSIS, DIFFERENTIAL; DISCRIMINANT ANALYSIS; DYSPLASTIC NEVUS SYNDROME; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MELANOMA; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NEVUS, PIGMENTED; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; SENSITIVITY AND SPECIFICITY; SKIN NEOPLASMS;

EID: 38349142814     PISSN: 0909752X     EISSN: 16000846     Source Type: Journal    
DOI: 10.1111/j.1600-0846.2007.00261.x     Document Type: Article

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