Zusammenfassung
In this paper, we present an alternating retrospective MRI reconstruction framework based on a parametrized motion model. An image recovery algorithm promoting sparsity is used in tandem with a numeric parameter search to iteratively reconstruct a sharp image. Additionally, we introduce a multiresolution strategy to restrict the numeric complexity. This algorithm is then tested in conjunction with a simple motion model on simulated data and provides robust and fast reconstruction of sharp images from severely corrupted k-spaces.
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© 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Parbs, T.J., Mӧller, A., Mertins, A. (2019). Retrospective Blind MR Image Recovery with Parametrized Motion Models. In: Handels, H., Deserno, T., Maier, A., Maier-Hein, K., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2019. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-25326-4_30
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DOI: https://doi.org/10.1007/978-3-658-25326-4_30
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