IMI/Publicaţii/CSJM/Ediţii/CSJM v.22, n.2 (65), 2014/

Characterization and pattern recognition of color images of dermatological ulcers: a pilot study

Authors: Lucas C. Pereyra, Sìlvio M. Pereira, Juliana P. Souza, Marco A. C. Frade, Rangaraj M. Rangayyan, Paulo M. Azevedo-Marques
Keywords: Color image processing, color medical images, color texture, content-based image retrieval, computer-aided diagnosis, image segmentation, dermatological ulcers, tissue composition analysis.


We present color image processing methods for the characterization of images of dermatological lesions for the purpose of content-based image retrieval (CBIR) and computer-aided diagnosis. The intended application is to segment the images and perform 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 following the red-yellow-black-white model. Automatic segmentation was performed by means of clustering using Gaussian mixture modeling, and its performance was evaluated by deriving the Jaccard coefficient between the automatically and manually segmented images. Statistical texture features were derived from cooccurrence matrices of RGB, HSI, L*a*b*, and L*u*v* color components. A retrieval engine was implemented using the k-nearest-neighbor classifier and the Euclidean, Manhattan, and Chebyshev distance metrics. Classification was performed by means of a metaclassifier using logistic regression. The average Jaccard coefficient after the segmentation step between the automatically and manually segmented images was 0.560, with a standard deviation of 0.220. The performance in CBIR was measured in terms of precision of retrieval, with average values of up to 0.617 obtained with the Chebyshev distance. The metaclassifier yielded an average area under the receiver operating characteristic curve of 0.772.

Lucas C. Pereyra, Juliana P. Souza, Marco A. C. Frade, Paulo M. Azevedo-Marques
Ribeirão Preto Medical School, University of São Paulo
Av. dos Bandeirantes 3900, Monte Alegre, 14049-900, Ribeirão Preto - SP, Brazil
E-mail: , , ,

Sìlvio M. Pereira
Bioengineering Interunits Graduate Course, University of São Paulo
São Carlos - SP, Brazil

Rangaraj M. Rangayyan
Department of Electrical and Computer Engineering, Schulich School of Engineer-
ing, University of Calgary, Calgary, Alberta, T2N 1N4, Canada


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