A primary morphological classifier for skin lesion images

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationFull Papers Proceedings
EditorsPaul Bourke, Vaclav Skala
PublisherUniversity of West Bohemia
Pages55-64
Number of pages10
Volume2701
EditionMay
ISBN (Electronic)9788086943497
StatePublished - Jan 1 2017
Event25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2017 - Plzen, Czech Republic
Duration: May 29 2017Jun 2 2017

Conference

Conference25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2017
CountryCzech Republic
CityPlzen
Period5/29/176/2/17

Keywords

  • Classification
  • Computer vision
  • Machine learning
  • Skin lesion

ASJC Scopus subject areas

  • Psychiatry and Mental health

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