Lesion border detection in Buruli ulcer images.

Rui Hu, Courtney M Queen, George Zouridakis
Author Information
  1. Rui Hu: Department of Electrical and Computer Engineering, Houston, TX 77004, USA.

Abstract

Buruli ulcer, a disease caused by infection with Mycobacterium ulcerans, is one of the most neglected but treatable tropical diseases. In this paper, a novel segmentation scheme is proposed to detect the border of Buruli lesions in cross-polarization dermoscopic images that were obtained under white light illumination. The method consists of three main steps: first, segmentations in different color spaces by thresholding are fused to form an initial contour, then a level set segmentation is applied to both the luminance and color components of the image, and finally, decisions for each pixel are made by a support vector machine classifier. Experimental results with 26 images show that the proposed methodology outperforms other state-of-art segmentation approaches for Buruli images.

Grants

  1. 1R21AR057921/NIAMS NIH HHS

MeSH Term

Automation
Buruli Ulcer
Humans

Word Cloud

Created with Highcharts 10.0.0BuruliimagessegmentationulcerproposedbordercolordiseasecausedinfectionMycobacteriumulceransoneneglectedtreatabletropicaldiseasespapernovelschemedetectlesionscross-polarizationdermoscopicobtainedwhitelightilluminationmethodconsiststhreemainsteps:firstsegmentationsdifferentspacesthresholdingfusedforminitialcontourlevelsetappliedluminancecomponentsimagefinallydecisionspixelmadesupportvectormachineclassifierExperimentalresults26showmethodologyoutperformsstate-of-artapproachesLesiondetection

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