A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images.
A fuzzy logic-based color histogram analysis technique is presented for discriminating benign skin lesions from malignant melanomas in dermatology clinical images. The approach utilizes a fuzzy set for benign skin lesion color, and alpha-cut and support set cardinality for quantifying a fuzzy ratio skin lesion color feature. Skin lesion discrimination results are reported for the fuzzy ratio and fusion with a previously determined percent melanoma color feature over a data set of 258 clinical images. For the fusion technique, alpha-cuts for the fuzzy ratio can be chosen to recognize over 93.30% of melanomas with approximately 15.67% false positive lesions.
Stanley
R Joe
RJ
Department of Electrical and Computer Engineering, University of Missouri-Rolla, 1870 Miner Circle, 127 Emerson Electric Company Hall, Rolla, MO 65409, USA. stanleyr@ece.umr.edu
Moss
Randy Hays
RH
Van Stoecker
William
W
Aggarwal
Chetna
C
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D017143:Fuzzy Logic; D006801:Humans; D008545:Melanoma / Q000175:diagnosis*; D012878:Skin Neoplasms / Q000175:diagnosis*; D012880:Skin Pigmentation