A Wide Spread of Algorithms for Automatic Segmentation of Dermoscopic Images
Currently, there is a great interest in the development of computer-aided diagnosis (CAD) systems for dermoscopic images. The segmentation step is one of the most important ones, since its accuracy determines the eventual success or failure of a CAD system. In this paper, different kinds of algorithms for the automatic segmentation of skin lesions in dermoscopic images were implemented and evaluated, namely automatic thresholding, k-means, mean-shift, region growing, gradient vector flow (GVF), and watershed. The segmentation methods were evaluated with three distinct metrics, using as ground truth a database of 50 images manually segmented by an expert dermatologist. Among the implemented segmentation approaches, the GVF snake method achieved the best segmentation performance.
KeywordsDermoscopy melanoma skin lesion image segmentation
Unable to display preview. Download preview PDF.
- 1.Argenziano, G., Soyer, H., Giorgio, V.D., Piccolo, D., et al.: Dermoscopy, an interactive atlas. EDRA Medical Publishing (2000), http://www.dermoscopy.org
- 3.Pagadala, P.: Tumor border detection in epiluminescence microscopy images. Master’s thesis, University of Missouri-Rolla (1998)Google Scholar
- 4.Celebi, M.E., Aslandogan, Y.A., Bergstresser, P.R.: Unsupervised border detection of skin lesion images. In: Int. Conf. on Information Technology: Coding and Computing, vol. 2, pp. 123–128 (2005)Google Scholar
- 9.Melli, R., Grana, C., Cucchiara, R.: Comparison of color clustering algorithms for segmentation of dermatological images. In: Proc. of the SPIE Medical Imaging, vol. 6144 (2006)Google Scholar
- 11.Barata, C., Marques, J.S., Rozeira, J.: Detecting the pigment network in dermoscopy images: a directional approach. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., pp. 5120–5123 (2011)Google Scholar
- 14.Suri, J.S., Wilson, D.L., Laxminarayan, S.: Handbook of Biomedical Image Analysis. Kluwer Academic/Plenum Publishers (2005)Google Scholar
- 15.Gonzalez, R.C., Woods, R.E.: Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River (2002)Google Scholar