  Purpose: To introduce a fast and improved direct reconstruction method for
multi-shot diffusion weighted (msDW) scans for high-resolution studies.
  Methods:Multi-shot EPI methods can enable higher spatial resolution for
diffusion MRI studies. Traditionally, such acquisitions required specialized
reconstructions involving phase compensation to correct for inter-shot motion
artifacts. The recently proposed MUSSELS reconstruction belongs to a new class
of parallel imaging-based methods that recover artifact-free DWIs from msDW
data without needing phase compensation. However, computational demands of the
MUSSELS reconstruction scales as the matrix size and the number of shots
increases, which hinders its practical utility for high-resolution
applications. In this work, we propose a computationally efficient formulation
using iterative reweighted least squares (IRLS) method. The new formulation is
not only fast but it enables to accommodate additional priors such as conjugate
symmetry property of the k-space data to improve the reconstruction. Using
whole-brain in-vivo data, we show the utility of the new formulation for
routine high-resolution studies with minimal computational burden.
  Results: The IRLS formulation provides about six times faster reconstruction
for matrix sizes 192x192 and 256x256, compared to the original implementations.
The reconstruction quality is improved by the addition of conjugate symmetry
priors that reduce blurring and preserves the high-resolution details from
partial Fourier acquisitions.
  Conclusion: The proposed method is shown to be computationally efficient to
enable routine high-resolution studies. The computational complexity matches
the traditional msDWI reconstruction methods and provides improved
reconstruction results.
