Abstract #2053

Noise Reduction in Accelerated Diffusion Spectrum Imaging Through Integration of SENSE Reconstruction Into Joint Reconstruction in Combination with Q-Space Compressed Sensing

Vladimir Golkov¹,², Tim Sprenger¹,³, Marion I. Menzel¹, Ek T. Tan⁴, Kevin F. King⁵, Christopher J. Hardy⁴, Luca Marinelli⁴, Daniel Cremers², Jonathan I. Sperl¹

¹GE Global Research, Garching n. Munich, Bavaria, Germany; ²Department of Computer Science, Technical University Munich, Garching n. Munich, Bavaria, Germany; ³IMETUM, Technical University Munich, Garching n. Munich, Bavaria, Germany; ⁴GE Global Research, Niskayuna, NY, United States; ⁵GE Healthcare, Waukesha, WI, United States

Sensitivity encoding (SENSE) reconstruction of diffusion weighted images (DWIs) in diffusion MRI is usually done independently for each DWI, without exploiting structural correlations between the DWIs. In this work, SENSE is incorporated into a joint reconstruction framework which models the prior knowledge of common smooth regions and edges in the DWIs. Image quality is improved in comparison to SENSE reconstruction, and even more so in combination with q-space compressed sensing.