Open Access
Issue
MATEC Web Conf.
Volume 76, 2016
20th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016)
Article Number 05002
Number of page(s) 8
Section Signal Processing
DOI https://doi.org/10.1051/matecconf/20167605002
Published online 21 October 2016
  1. E. Claridge, P.N. Hall, M. Keefe, J.P. Allen, Shape Analysis for Classification of Malignant Melanoma, JBE 14 (3), 229–234 (1992) [Google Scholar]
  2. K. Klein, T. Maier, V.C. Hirschfeld-Warneken, J.P. Spatz, Marker-Free Phenotyping of Tumor Cells by Fractal Analysis of Reflection Interference Contrast Microscopy Images, NL, ACS Publications, American Chemical Society, dx.doi.org/10.1021/nl4030402 | Nano Lett. 2013, 13, 5474–5479 (2013) [Google Scholar]
  3. P.Y. Kim, K.M. Iftekharuddin, P.G. Davey, M. Toth, A. Garas, G. Hollo, E.A. Essock, Novel Fractal Feature-Based Multiclass Glaucoma Detection and Progression Prediction, BHI, IEEE Journal of, 17, no.2, pp.269-276 (March 2013), doi: 10.1109/TITB.2012.2218661 [Google Scholar]
  4. M. Mastrolonardo, E. Conte, J.P. Zbilut, 2006. A fractal analysis of skin pigmented lesions using the novel tool of the variogram technique, CSF, 28, 1119–1135 (2006) [Google Scholar]
  5. A. Piantanelli, P. Maponi, L. Scalise, S. Serresi, A. Cialabrini, A. Basso, Fractal characterisation of boundary irregularity in skin pigmented lesions, MBEC. Jul; 43 (4), 436–42 (2005) [Google Scholar]
  6. E. Zagrouba, W. Barhoumi, A preliminary approach for the automated recognition of malignant melanoma, IAS, 23, 121–135 (2004) [Google Scholar]
  7. R. Dobrescu, M. Dobrescu, S. Mocanu and D. Popescu, Medical Images Classification for Skin Cancer Diagnosis Based on Combined Texture and Fractal Analysis, WSEAS Transactions on Biology and Biomedicine, 7, no. 3, pp. 223–232 (2010) [Google Scholar]
  8. R. Lopes, N. Betrouni, Fractal and multifractal analysis: A review, Medical Image Analysis, 13, 634–649 (2009) [CrossRef] [Google Scholar]
  9. S. Criscuoli, M.P. Ras, I. Ermolli and M. Centrone, On the reliability of the fractal dimension measure of solar magnetic features and on its variation with solar activity, AA, 461, 331-338 (2007), DOI: 10.1051/0004-6361:20065951 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. H. Ahammer, T.T.J. DeVaney, The influence of edge detection algorithms on the estimation of the fractal dimension of binary digital images, C, 14(1):183–8 (2004) [Google Scholar]
  11. B. Braverman, M. Tambasco, Scale-Specific Multifractal Medical Image Analysis, CMMM, 2013, Hindawi Publishing Corporation, Article ID 262931, 11 pages, http://dx.doi.org/10.1155/2013/262931 (2013) [Google Scholar]
  12. A.R. Martin, N. Sabathiel, H. Ahammer, Noise dependency of algorithms for calculating fractal dimensions in digital images, CSF, 78, 39–46, (2015) [Google Scholar]
  13. B. Mandelbrot, The Fractal Geometry of Nature, (W. H. Freeman, San Francisco, 1982) [Google Scholar]
  14. K. J. Falconer, Fractal Geometry. Mathematical foundations and Applications, John Wiley and Sons, England (1990) [Google Scholar]
  15. M. F. Barnsley, Fractals everywhere, Academic Press, USA (1988) [Google Scholar]
  16. E. Hadzieva, D. C. Bogatinoska, Lj. Gjergjeska, M. Shuminoska, R. Petreski, Review of the Software Tools for Estimating the Fractal Dimension, S. Loshkovska, S. Koceski (Editors): ICT Innovations 2015, Web Proceedings, ISSN 1857-7288, p. 201–211 (2015) [Google Scholar]
  17. O. Zmeškal, M. Vesely, M. Nezadal, M. Buchniček, Fractal Analysis of Image Structures, HarFA - Harmonic and Fractal Image Analysis, 3–5, (2001) [Google Scholar]
  18. M. E. Celebi, A. Aslandogan, W. V. Stoecker, Unsupervised Border Detection in Dermoscopy Images, SRT, 13(4): 454–462 (2007) [Google Scholar]
  19. M. E. Celebi, H. Kingravi, H. Iyatomi, A. Aslandogan, W. V. Stoecker, R. H. Moss, Border Detection in Dermoscopy Images Using Statistical Region Merging, SRT, 14(3): 347–353 (2008) [Google Scholar]
  20. M. E. Celebi, H. Iyatomi, G. Schaefer, W. V. Stoecker, Lesion Border Detection in Dermoscopy Images, CMIG, 33(2): 148–153 (2009) [Google Scholar]
  21. M. E. Celebi, Q. Wen, S. Hwang, H. Iyatomi, G. Schaefer, Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods, Skin Research and Technology, 19(1): e252–258 (2013) [CrossRef] [Google Scholar]
  22. S. Angenent, E. Pichon, A. Tannenbaum, Mathematical Methods in Medical Image Processing, BAMS. 43, 365–396 (2006). [CrossRef] [Google Scholar]

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