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Abstract #0463

Diffusion Acceleration with Gaussian process Estimated Reconstruction (DAGER)

Wenchuan Wu1, Peter J Koopmans2, Jesper Andersson1, and Karla L Miller1

1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 2Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany

Diffusion acceleration is a challenging task, particularly when using simultaneous multi-slice (SMS) imaging with in-plane acceleration. In this work, we develop a method termed DAGER: Diffusion Acceleration with Gaussian process Estimated Reconstruction, to improve SMS with in-plane acceleration, achieving a total acceleration factor of 12 (MB=4, R=3). In addition, DAGER reconstruction doesn't cause major degradation of angular resolution, indicating the Gaussian process model used in DAGER can accurately estimating the degree of local smoothness in q-space.

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