Abstract
In this work, a new method for noise reduction in low dose DSA imaging is presented. The algorithm extends an existing approach using the low rank nature of DSA image series to enable considerable reduction of radiation dose while maintaining low image noise level and preserving spatial resolution and temporal dynamics of the DSA series. The algorithm is based on the singular value decomposition (SVD) using a pixel adaptive approach for the noise reduction. For validation of the method an in vivo animal study is examined
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© 2017 Springer-Verlag GmbH Deutschland
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Menger, N., Elsässer, T., Chen, GH., Manhart, M. (2017). Noise Reduction in Low Dose DSA Imaging Using Pixel Adaptive SVD-Based Approach. In: Maier-Hein, geb. Fritzsche, K., Deserno, geb. Lehmann, T., Handels, H., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2017. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54345-0_15
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DOI: https://doi.org/10.1007/978-3-662-54345-0_15
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Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-54344-3
Online ISBN: 978-3-662-54345-0
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