Abstract
Selected methods of image processing have been applied to expert system supporting the process of identifying medical images. Fourier transform is well known tool for many applications in the processing of images in many fields of science and technology, also in medicine. In this case the image processing consists in spatial frequencies analysis of Fourier transforms of medical images. Skin lesions are studied on the base of their images and it seems that Fourier transformation is the right toll for such research. The distributions of selected colors in Fourier transform images are studied.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Andrews, R., Bajcar, S., Grzymała-Busse, J.W., Hippe, Z.S., Whiteley, C.: Optimization of the ABCD formula for Melanoma diagnosis using C4.5, a data mining system. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 630–636. Springer, Heidelberg (2004)
Bogomolny, R., Huleihel, M., Suproun, Y., Mordechai, S.: Early spectral changes of cellular malignant transformation using Fourier transform infrared microspectroscopy. Journal of Biomedical Optics 12, 024003 (2007)
Colot, O., Devinoy, R., Sombo, A., de Brucq, D.: A colour image processing method for melanoma detection. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 562–569. Springer, Heidelberg (1998)
Cooley, J.W., Tookey, J.W.: An algorithm for the machine calculation of complex Fourier series. Mathematics of Computations 19, 297–301 (1965)
Friedman, R.J., Rigel, D.S., Kopf, A.W.: Early detection of malignant melanoma: the role of physician examination and self-examination of the skin. CA Cancer J. Clin. 35, 130–151 (1985)
Ganster, H., Pinz, P., Rohrer, R., Wildling, E., Binder, M., Kittler, H.: Automated melanoma recognition. IEEE Transactions on Medical Imaging 20, 233–239 (2001)
Grzymała-Busse, J.W.: A new version of the rule induction system LERS. Fundamenta Informaticae 31, 27–39 (1997)
Grzymała-Busse, J.W.: LERS A system for learning from examples based on rough sets. In: Słowiński, R. (ed.) Intelligent Decision Support. Handbook of Application and Advances of the Rough Sets Theory Rough Sets, pp. 3–18. Kluwer Academic Publishers, Dordrecht (1992)
Grzymała-Busse, J.W., Hippe, Z.S., Mroczek, T.: Belief rules vs. decision rules: a preliminary appraisal of the problem. In: Kłopotek, M.A., et al. (eds.) Proc. of the International IIS, Poland, pp. 431–435 (2005)
Marks II, R.J.: Handbook of fourier analysis and its applications, ch. 5-8. Oxford University Press, Chapters (2009)
Schindewolf, T., Stolz, W., Albert, R., Abmayr, W., Harms, H.: Classification of melanocytic lesions with color and texture analysis using digital image processing. Anal. Quant. Cytol. Histol. 15, 1–11 (1993)
Sikorski, J.: Identification of malignant melanoma by wavelet analysis. In: Proc. of Student/Faculty Research Day, CSIS, Pace University, USA, pp. 10.1–10.9 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Sokołowski, A., Pardela, T. (2014). Application of Fourier Transforms in Classification of Medical Images. In: Hippe, Z., Kulikowski, J., Mroczek, T., Wtorek, J. (eds) Human-Computer Systems Interaction: Backgrounds and Applications 3. Advances in Intelligent Systems and Computing, vol 300. Springer, Cham. https://doi.org/10.1007/978-3-319-08491-6_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-08491-6_16
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08490-9
Online ISBN: 978-3-319-08491-6
eBook Packages: EngineeringEngineering (R0)