| Literature DB >> 24786720 |
Mounika Lingala1, R Joe Stanley2, Ryan K Rader3, Jason Hagerty4, Harold S Rabinovitz5, Margaret Oliviero6, Iqra Choudhry7, William V Stoecker8.
Abstract
Fuzzy logic image analysis techniques were used to analyze three shades of blue (lavender blue, light blue, and dark blue) in dermoscopic images for melanoma detection. A logistic regression model provided up to 82.7% accuracy for melanoma discrimination for 866 images. With a support vector machines (SVM) classifier, lower accuracy was obtained for individual shades (79.9-80.1%) compared with up to 81.4% accuracy with multiple shades. All fuzzy blue logic alpha cuts scored higher than the crisp case. Fuzzy logic techniques applied to multiple shades of blue can assist in melanoma detection. These vector-based fuzzy logic techniques can be extended to other image analysis problems involving multiple colors or color shades.Entities:
Keywords: Blue area; Dermoscopy; Dysplastic nevi; Fuzzy logic; Image analysis; Melanoma
Mesh:
Year: 2014 PMID: 24786720 PMCID: PMC4287461 DOI: 10.1016/j.compmedimag.2014.03.007
Source DB: PubMed Journal: Comput Med Imaging Graph ISSN: 0895-6111 Impact factor: 4.790