title: Classification of melanoma using tree structured wavelet transforms.
abstract: This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.
authors.affiliation: Department of Electrical and Computer Engineering, New Jersey Institute of Technology, University Heights, 07102, Newark, NJ, USA.
authors.forename: Sachin V
authors.initials: SV
authors.lastname: Patwardhan
authors.forename: Atam P
authors.initials: AP
authors.lastname: Dhawan
authors.forename: Patricia A
authors.initials: PA
authors.lastname: Relue
mesh_terms: D006801:Humans; D008545:Melanoma / Q000145:classification*; D008962:Models, Theoretical