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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