Computer-Supported Diagnosis of Melanoma in Profilometry

TitleComputer-Supported Diagnosis of Melanoma in Profilometry
Publication TypeJournal Article
Year of Publication1999
AuthorsHandels H., Ross T., Kreusch J., Wolff H.H., Pöppl S.J.
JournalMethods of information in medicine
Date Published1999 Mar
Publication Languageeng
KeywordsDiagnosis, Differential, Humans, Image Interpretation, Computer-Assisted, Melanoma, Neural Networks (Computer), Nevus, Skin Neoplasms, Surface Properties

Laser profilometry offers new possibilities to improve non-invasive tumor diagnostics in dermatology. In this paper, a new approach to computer-supported analysis and interpretation of high-resolution skin-surface profiles of melanomas and nevocellular nevi is presented. Image analysis methods are used to describe the profile's structures by texture parameters based on co-occurrence matrices, features extracted from the Fourier power spectrum, and fractal features. Different feature selection strategies, including genetic algorithms, are applied to determine the best possible subsets of features for the classification task. Several architectures of multilayer perceptrons with error back-propagation as learning paradigm are trained for the automatic recognition of melanomas and nevi. Furthermore, network-pruning algorithms are applied to optimize the network topology. In the study, the best neural classifier showed an error rate of 4.5% and was obtained after network pruning. The smallest error rate in all, of 2.3%, was achieved with nearest neighbor classification.

PubMed Link

Alternate JournalMethods Inf Med
Created at November 19, 2012 - 3:39pm by Kulbe.


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