A textured scale-based approach to melanocytic skin lesions in dermoscopy

Fonseca-Pinto, Rui; Marlene Machado

http://hdl.handle.net/10400.8/13946

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Authors

Fonseca-Pinto, Rui

Marlene Machado

Abstract(s)

Melanoma is the most dangerous and lethal form of human skin cancer and the early detection is a fundamental key for its successful management. In recent years the use of automatic classification algorithms in the context of Computer Aided Diagnosis (CAD) systems have been an important tool, by improving quantification metrics and also assisting in the decision regarding lesion management. This paper presents a novel and robust textured-based approach to detect melanomas among melanocytic images obtained by dermoscopy, using Local Binary Pattern Variance (LBPV) histograms after the Bidimensional Empirical Mode Decomposition (BEMD) scale-based decomposition methodology. The results show that it is possible to develop a robust CAD system for the classification of dermoscopy images obtained from different databases and acquired in diverse conditions. After the initial texture-scale based classification a post-processing refinement is proposed using reticular pattern and color achieving to 97.83, 94.44 and 96.00 for Sensitivity, Specificity and Accuracy.

Keywords

Lesions Malignant tumors Training Two dimensional displays Image color analysis Feature extraction Histograms

URI

http://hdl.handle.net/10400.8/13946

Citation

R. Fonseca-Pinto and M. Machado, "A textured scale-based approach to melanocytic skin lesions in dermoscopy," 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, Croatia, 2017, pp. 279-282, doi: 10.23919/MIPRO.2017.7973434