A Wide Spread of Algorithms for Automatic Segmentation of Dermoscopic Images

  • Pedro M. Ferreira
  • Teresa Mendonça
  • Paula Rocha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7887)


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.


Dermoscopy melanoma skin lesion image segmentation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Argenziano, G., Soyer, H., Giorgio, V.D., Piccolo, D., et al.: Dermoscopy, an interactive atlas. EDRA Medical Publishing (2000),
  2. 2.
    Campos-do-Carmo, G., Ramos-e-Silva, M.: Dermoscopy: basic concepts. Int. J. Dermatol. 47(7), 712–719 (2008)CrossRefGoogle Scholar
  3. 3.
    Pagadala, P.: Tumor border detection in epiluminescence microscopy images. Master’s thesis, University of Missouri-Rolla (1998)Google Scholar
  4. 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
  5. 5.
    Celebi, M.E., Kingravi, H.A., Iyatomi, H., Aslandogan, Y.A., et al.: Border detection in dermoscopy images using statistical region merging. Skin Research and Technology 14(3), 347–353 (2008)CrossRefGoogle Scholar
  6. 6.
    Chung, D.H., Sapiro, G.: Segmenting skin lesions with partial-differential-equations-based image processing algorithms. IEEE Transactions on Medical Imaging 19(7), 763–767 (2000)CrossRefGoogle Scholar
  7. 7.
    Erkol, B., Moss, R.H., Stanley, R.J., Stoecker, W.V., Hvatum, E.: Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes. Skin Research and Technology 11(1), 17–26 (2005)CrossRefGoogle Scholar
  8. 8.
    Schmid, P.: Segmentation of digitized dermatoscopic images by two-dimensional color clustering. IEEE Transactions on Medical Imaging 18(2), 164–171 (1999)CrossRefGoogle Scholar
  9. 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
  10. 10.
    Silveira, M., Nascimento, J.C., Marques, J.S., Marçal, A.R.S., et al.: Comparison of segmentation methods for melanoma diagnosis in dermoscopy images. IEEE Journal of Selected Topics in Signal Processing 3(1), 35–45 (2009)CrossRefGoogle Scholar
  11. 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
  12. 12.
    Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst., Man, Cybern. 9(1), 62–66 (1979)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Zack, G.W., Rogers, W.E., Latt, S.A.: Automatic measurement of sister chromatid exchange frequency. J. Histochem. Cytochem. 25(7), 741–753 (1977)CrossRefGoogle Scholar
  14. 14.
    Suri, J.S., Wilson, D.L., Laxminarayan, S.: Handbook of Biomedical Image Analysis. Kluwer Academic/Plenum Publishers (2005)Google Scholar
  15. 15.
    Gonzalez, R.C., Woods, R.E.: Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pedro M. Ferreira
    • 1
    • 2
  • Teresa Mendonça
    • 1
    • 3
  • Paula Rocha
    • 2
    • 3
  1. 1.Faculdade de CiênciasUniversidade do PortoPortugal
  2. 2.Faculdade de EngenhariaUniversidade do PortoPortugal
  3. 3.Center for Research Development in Mathematics and ApplicationsPortugal

Personalised recommendations