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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Classification of Color Images of Dermatological Ulcers

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Author(s):
Pereira, Silvio M. [1] ; Frade, Marco A. C. [2] ; Rangayyan, Rangaraj M. [3] ; Azevedo-Marques, Paulo M. [2]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Sao Carlos Sch Engn, BR-13566590 Sao Paulo - Brazil
[2] Univ Sao Paulo, Sch Med Ribeirao Preto, BR-14048900 Sao Paulo - Brazil
[3] Univ Calgary, Schulich Sch Engn, Calgary, AB T2N 1N4 - Canada
Total Affiliations: 3
Document type: Journal article
Source: IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS; v. 17, n. 1, p. 136-142, JAN 2013.
Web of Science Citations: 11
Abstract

We present color image processing methods for the analysis of images of dermatological lesions. The focus of this study 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 previously. Indexing of the images was performed based on statistical texture features derived from cooccurrence matrices of the red, green, and blue (RGB), hue, saturation, and intensity (HSI), 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. (AU)