Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods. Issue 1 (7th June 2012)

• Record Type: Journal Article
• Authors: Emre Celebi, M.; Wen, Quan; Hwang, Sae; Iyatomi, Hitoshi; Schaefer, Gerald
• Is Part Of: Skin research and technology. Volume 19:Issue 1(2013)
• Page Start: e252
• Page End: e258
• Publication Date: 2012-06-07
• Subjects: Skin -- Research -- Periodicals; Skin -- Diseases -- Periodicals; Skin -- Physiology -- Periodicals; 616.5
• DOI: 10.1111/j.1600-0846.2012.00636.x
• Languages: English
• ISSNs: 0909-752X

Abstract

<abstract abstract-type="main" id="srt634-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="srt636-sec-0001" sec-type="section"> <title>Background</title> <p>Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, automated analysis of dermoscopy images has become an important research area. Border detection is often the first step in this analysis. In many cases, the lesion can be roughly separated from the background skin using a thresholding method applied to the blue channel. However, no single thresholding method appears to be robust enough to successfully handle the wide variety of dermoscopy images encountered in clinical practice.</p> </sec> <sec id="srt636-sec-0002" sec-type="section"> <title>Methods</title> <p>In this article, we present an automated method for detecting lesion borders in dermoscopy images using ensembles of thres holding methods.</p> </sec> <sec id="srt636-sec-0003" sec-type="section"> <title>Conclusion</title> <p>Experiments on a difficult set of 90 images demonstrate that the proposed method is robust, fast, and accurate when compared to nine state‐of‐the‐art methods.</p> </sec> </abstract>