Fast Simultaneous Multi-Slice Multi-Shell Diffusion Tensor Imaging with Model-based Reconstruction

Multi-Shell DTI suffers from low SNR for high b-value data and prolonged scan time. The Gaussian noise assumption is
typically violated due to multi-coil imaging and magnitude forming thus requiring special treatment to avoid biases in
the DTI estimates. To this end, we propose a model-based reconstruction technique to exploit the Gaussian noise in the
raw k-space data and enable acceleration of the DTI measurement. We show the acceleration potential and quantitative
accuracy of the proposed method for mono- and bi-exponential fitting approaches on freely available DTI data and full
brain DTI measurements of one healthy volunteer.