Abstract
The aim of our research is to extract local subtle directional texture orientation on mammographic images using a set of differentiating features calculated in various transformation domains. The main goal in this paper was to establish the usefulness of multiscale transformations, in particular the complex wavelet transform in automatic recognition of indefinite directional pathologies on mammograms. Our initial test was conducted on ROIs of mammograms containing one of typical breast cancer signs - architectural distortions (33 ROIs out of all analyzed 289 ROIs). The promising results have been achieved. It seems that the complex wavelet transform is effective domain to extract well-differentiating features.
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References
Ayres, F.J., Rangayyan, R.M.: Characterization of architectural distortion in mammograms. IEEE Engineering in Medicine and Biology Magazine 24, 59–67 (2005)
Baker, J.A., Rosen, E.L., Lo, J.Y., Gimenez, E.I., Walsh, R., Scott Soo, M.: Computer-aided detection in screening mammography: sensitivity of commercial CAD system for detecting architectural distortion. American Journal of Roentgenology 181, 1083–1088 (2003)
Birdwell, R.L., Bandodkar, P., Ikeda, D.M.: Computer-aided detection with screening mammography in a University Hospital Setting. Radiology 236, 451–457 (2005)
Bovik, A.C., Markey, M.K., Sampat, M.P., Whitman, G.J.: Evidence based detection of speculated masses and architectural distortions. In: Medical Imaging: Image Processing, Proc. SPIE, vol. 5747, pp. 26–37 (2005)
Digital Database for Screening Mammography (DDSM). University of South Florida, Florida, USA, http://marathon.csee.usf.edu/Mammography/Database.html
Dziukowa, J. (red.): Mammografia w diagnostyce raka sutka, Warszawa (1998)
Endo, T., Fujita, H., Hara, T., Ichikawa, T., Iwase, T., Matsubara, T.: Automated detection method for architectural distortion areas on mammograms based on morphological processing and surface analysis. In: Medical Imaging: Image Processing, Proc. SPIE, vol. 5370, p. 920 (2004)
Kingsbury, N.G.: The dual-tree complex wavelet transform: A new efficient tool for image restoration and enhancement. In: Proc. European Signal Processing Conference, EUSIPCO 1998, Rhodes, pp. 319–322 (1998)
Koronacki, J., Ćwik, J.: Statystyczne metody uczące się. Akademicka Oficyna Wydawnicza EXIT. Wydanie drugie, Warszawa (2008)
Jasionowska, M., Przelaskowski, A., Rutczynska, A., Wroblewska, A.: A Two-Step Method for Detection of Architectural Distortions in Mammograms. In: Piętka, E., Kawa, J. (eds.) Information Technologies in Biomedicine. AISC, vol. 69, pp. 73–84. Springer, Heidelberg (2010)
Jasionowska, M., Przelaskowkski, A.: Multiscale modeling of local directional mammogram findings. Journal of Medical Informatics and Technologies 17, 183–190 (2010)
Majumdar, A., Bhattachatya, A.: A comparative study in wavelets, curvelets and contourlets as feature sets for pattern recognition. The International Arab Journal of Information Technology 6(1), 47–51 (2009)
Musoko, V., Prochazka, A.: Complex wavelet transform in signal and image analysis. In: Proc. of 6th Int. Sc.-Techn. Conference Process Control (2004)
Rangayyan, R.M., Ayres, F.J.: Gabor filters and phase portraits for the detection of architectural distortion in mammograms. Medical and Biological Engineering 44(10), 883–894 (2006)
Rangayyan, R.M., Prajna, S., Ayres, F.J., Leo Desautels, J.E.: Detection of architectural distortion in prior screening mammograms using Gabor filters, phase portraits, fractal dimension and texture analysis. International Journal of Computer Assisted Radiology and Surgery 2(6), 347–361 (2008)
Tadeusiewicz, R.: What Does it Means ”Automatic Understanding of the Images”? In: Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, IEEE Imaging Systems Technical Committee (2007)
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Jasionowska, M., Przelaskowski, A. (2012). Subtle Directional Mammographic Findings in Multiscale Domain. In: Piętka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Lecture Notes in Computer Science(), vol 7339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31196-3_8
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DOI: https://doi.org/10.1007/978-3-642-31196-3_8
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