Paper
26 March 2007 Fast and accurate border detection in dermoscopy images using statistical region merging
M. Emre Celebi, Hassan A. Kingravi, Hitoshi Iyatomi, JeongKyu Lee, Y. Alp Aslandogan, William Van Stoecker, Randy Moss, Joseph M. Malters, Ashfaq A. Marghoob
Author Affiliations +
Abstract
As a result of advances in skin imaging technology and the development of suitable image processing techniques during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of melanoma. Automated border detection is one of the most important steps in this procedure, since the accuracy of the subsequent steps crucially depends on it. In this paper, a fast and unsupervised approach to border detection in dermoscopy images of pigmented skin lesions based on the Statistical Region Merging algorithm is presented. The method is tested on a set of 90 dermoscopy images. The border detection error is quantified by a metric in which a set of dermatologist-determined borders is used as the ground-truth. The proposed method is compared to six state-of-the-art automated methods (optimized histogram thresholding, orientation-sensitive fuzzy c-means, gradient vector flow snakes, dermatologist-like tumor extraction algorithm, meanshift clustering, and the modified JSEG method) and borders determined by a second dermatologist. The results demonstrate that the presented method achieves both fast and accurate border detection in dermoscopy images.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Emre Celebi, Hassan A. Kingravi, Hitoshi Iyatomi, JeongKyu Lee, Y. Alp Aslandogan, William Van Stoecker, Randy Moss, Joseph M. Malters, and Ashfaq A. Marghoob "Fast and accurate border detection in dermoscopy images using statistical region merging", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65123V (26 March 2007); https://doi.org/10.1117/12.709073
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Cited by 40 scholarly publications.
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KEYWORDS
Skin

Image segmentation

Melanoma

Error analysis

Image processing

Digital filtering

Detection and tracking algorithms

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