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Skin Res Technol. 2008 Aug;14(3):347-53. doi: 10.1111/j.1600-0846.2008.00301.x.

Border detection in dermoscopy images using statistical region merging.

Author information

1
Department of Computer Science, Louisiana State University in Shreveport, Shreveport, LA 71115, USA. ecelebi@lsus.edu

Abstract

BACKGROUND:

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, because the accuracy of the subsequent steps crucially depends on it.

METHODS:

In this article, we present a fast and unsupervised approach to border detection in dermoscopy images of pigmented skin lesions based on the statistical region merging algorithm.

RESULTS:

The method is tested on a set of 90 dermoscopy images. The border detection error is quantified by a metric in which three sets of dermatologist-determined borders are used as the ground-truth. The proposed method is compared with four state-of-the-art automated methods (orientation-sensitive fuzzy c-means, dermatologist-like tumor extraction algorithm, meanshift clustering, and the modified JSEG method).

CONCLUSION:

The results demonstrate that the method presented here achieves both fast and accurate border detection in dermoscopy images.

PMID:
19159382
PMCID:
PMC3160669
DOI:
10.1111/j.1600-0846.2008.00301.x
[Indexed for MEDLINE]
Free PMC Article

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