Abstract
We present a method to prompt a clinician to “suspicious” dense regions in temporal mammogram sequences. The particular context that we envisage is mammogram screening, when the clinician compares the most recent mammogram to previous ones in order to detect significant changes. The method uses anisotropic filtering as a pre-processing step in order to significantly reduce the number of candidate masses, while preserving the important anatomical information about each mass. The method has already been tested on 15 temporal pairs, where pathology has been diagnosed in the most recent image.
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References
Linguraru, M.G. Brady, J.M. Yam, M.: Filtering hint Images for the Detection of Microcalcifications. In Niessen, W. Viergever, M. (eds.): Medical Image Computing and Computer-Assited Intervention 2001, Lecture Notes in Computer Science, Vol. 2208. Springer-Verlag, Berlin Heidelberg New York (2001) 629–636
Marias, K. Behrenbruch, C.P. Brady, M. Parbhoo, S. Seifalian, A.: Multi-Scale Landmark Selection for Improved Registration of Temporal Mammograms. In Yaffe, M.J. (ed.): International Workshop on Digital Mammography 2000, Medical Physics Publishing, Madison (2000) 580–586
Weickert, J.: Anisotropic Diffusion in Image Processing. B.G. Teubner, Stuttgart (1998)
Wolfe, J.N.: Breast Patterns as an Index of Risk for Developing Breast Cancer. American Journal of Roentgenology, 126 (1976) 1130–1139
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© 2003 Springer-Verlag Berlin Heidelberg
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Linguraru, M.G., Marias, K., Brady, M. (2003). Temporal Mass Detection. In: Peitgen, HO. (eds) Digital Mammography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59327-7_81
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DOI: https://doi.org/10.1007/978-3-642-59327-7_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-63936-4
Online ISBN: 978-3-642-59327-7
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