A primary morphological classifier for skin lesion images

Jules Matthew A. Macatangay, Conrado R. Ruiz, Richard P. Usatine

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1 Cita (Scopus)

Resumen

Classifying skin lesions, abnormal changes in skin, into their morphologies is the first step in diagnosing skin diseases. In dermatology, morphology is a categorization of a skin lesion's structure and appearance. Rather than directly classifying skin diseases, this research aims to explore classifying skin lesion images into primary morphologies. For preprocessing, k-means clustering for image segmentation and illumination equalization were applied. Additionally, features utilized considered color, texture, and shape. For classification, k-Nearest Neighbors, Decision Trees, Multilayer Perceptron, and Support Vector Machines were used. To evaluate the prototype, 10-fold cross validation was applied over a dataset assembled from online resources. In experimentation, the morphologies considered were macule, nodule, papule, and plaque. Moreover, different feature subsets were tested through feature selection experiments. Experimental results on the 4-class and 3-class tests show that of the classifiers selected, Decision Trees were best, having a Cohen's kappa of 0.503 and 0.558 respectively.

Idioma originalInglés
Título de la publicación alojadaFull Papers Proceedings
EditoresPaul Bourke, Vaclav Skala
EditorialUniversity of West Bohemia
Páginas55-64
Número de páginas10
Volumen2701
EdiciónMay
ISBN (versión digital)9788086943497
EstadoPublicada - 2017
Publicado de forma externa
Evento25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2017 - Plzen, República Checa
Duración: 29 may 20172 jun 2017

Conferencia

Conferencia25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2017
País/TerritorioRepública Checa
CiudadPlzen
Período29/05/172/06/17

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