Abstract
In this paper we propose a new log-chromaticity 2-D colour space, an extension of previous approaches, which succeeds in removing confounding factors from dermoscopic images: (i) the effects of the particular camera characteristics for the camera system used in forming RGB images; (ii) the colour of the light used in the dermoscope; (iii) shading induced by imaging non-flat skin surfaces; (iv) and light intensity, removing the effect of light-intensity falloff toward the edges of the dermoscopic image. In the context of a blind source separation of the underlying colour, we arrive at intrinsic melanin and hemoglobin images, whose properties are then used in supervised learning to achieve excellent malignant vs. benign skin lesion classification. In addition, we propose using the geometric-mean of colour for skin lesion segmentation based on simple grey-level thresholding, with results outperforming the state of the art.
http://www.sfu.ca/~amadooei/research/publication/miccai2012.html
Description: This page contains supplementary materials; such as sample output images, Matlab code, and links to other related projects.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Henning, J.S., Dusza, S.W., Wang, S.Q., Marghoob, A.A., Rabinovitz, H.S., Polsky, D., Kopf, A.W.: The CASH (color, architecture, symmetry, and homogeneity) algorithm for dermoscopy. J. of the Amer. Acad. of Dermatology 56, 45–52 (2007)
Claridge, E., Cotton, S., Hall, P., Moncrieff, M.: From colour to tissue histology: Physics-based interpretation of images of pigmented skin lesions. Med. Im. Anal. 7, 489–502 (2003)
Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley and Sons, Inc., New York (2001)
Tsumura, N., Ojima, N., Sato, K., Shiraishi, M., Shimizu, H., Nabeshima, H., Akazaki, S., Hori, K., Miyake, Y.: Image-based skin color and texture analysis/synthesis by extracting hemoglobin and melanin information in the skin. ACM Trans. Graph. 22, 770–779 (2003)
Tsumura, N., Haneishi, H., Miyake, Y.: Independent-component analysis of skin color image. J. of the Optical Soc. of Amer. A 16, 2169–2176 (1999)
Kang, H.R.: Color technology for electronic imaging systems. SPIE Optical Eng. Press (1997)
Hiraoka, M., Firbank, M., Essenpreis, M., Cope, M., Arrige, S.R., Zee, P.V.D., Delpy, D.T.: A Monte Carlo investigation of optical pathlength in inhomogeneous tissue and its application to near-infrared spectroscopy. Phys. Med. Biol. 38, 1859–1876 (1993)
Finlayson, G.D., Drew, M.S., Lu, C.: Intrinsic Images by Entropy Minimization. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004, Part III. LNCS, vol. 3023, pp. 582–595. Springer, Heidelberg (2004)
Finlayson, G.D., Drew, M.S., Funt, B.V.: Spectral sharpening: sensor transformations for improved color constancy. J. Opt. Soc. Am. A 11(5), 1553–1563 (1994)
Sadeghi, M., Razmara, M., Wighton, P., Lee, T., Atkins, M.: Modeling the Dermoscopic Structure Pigment Network Using a Clinically Inspired Feature Set. In: Liao, H., Eddie Edwards, P.J., Pan, X., Fan, Y., Yang, G.-Z. (eds.) MIAR 2010. LNCS, vol. 6326, pp. 467–474. Springer, Heidelberg (2010)
Haralick, R.M., Shapiro, L.G.: Computer and Robot Vision, vol. 1, p. 459. Addison-Wesley, New York (1992)
Wighton, P., Sadeghi, M., Lee, T.K., Atkins, M.S.: A Fully Automatic Random Walker Segmentation for Skin Lesions in a Supervised Setting. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part II. LNCS, vol. 5762, pp. 1108–1115. Springer, Heidelberg (2009)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. on Systems, Man and Cybernetics 9(1), 62–66 (1979)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: WEKA data mining software (2001), http://www.cs.waikato.ac.nz/ml/weka/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Madooei, A., Drew, M.S., Sadeghi, M., Atkins, M.S. (2012). Intrinsic Melanin and Hemoglobin Colour Components for Skin Lesion Malignancy Detection. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33415-3_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-33415-3_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33414-6
Online ISBN: 978-3-642-33415-3
eBook Packages: Computer ScienceComputer Science (R0)