IEEE J Biomed Health Inform - Classification of color images of dermatological ulcers.

Tópicos

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Resumo

We present color image processing methods for the analysis of images of dermatological lesions. The focus of the present work is on the application of feature extraction and selection methods for classification and analysis of the tissue composition of skin lesions or ulcers, in terms of granulation (red), fibrin (yellow), necrotic (black), callous (white), and mixed tissue composition. The images were analyzed and classified by an expert dermatologist into the classes mentioned above. Indexing of the images was performed based on statistical texture features derived from cooccurrence matrices of the RGB (Red, Green, and Blue), HSI (Hue, Saturation, and Intensity), L*a*b*, and L*u*v* color components. Feature selection methods were applied using the Wrapper algorithm with different classifiers. The performance of classification was measured in terms of the percentage of correctly classified images and the area under the receiver operating characteristic curve, with values of up to 73.8% and 0.82, respectively.

Resumo Limpo

present color imag process method analysi imag dermatolog lesion focus present work applic featur extract select method classif analysi tissu composit skin lesion ulcer term granul red fibrin yellow necrot black callous white mix tissu composit imag analyz classifi expert dermatologist class mention index imag perform base statist textur featur deriv cooccurr matric rgb red green blue hsi hue satur intens lab luv color compon featur select method appli use wrapper algorithm differ classifi perform classif measur term percentag correct classifi imag area receiv oper characterist curv valu respect

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