SMS MUSSELS: A navigator‐free reconstruction for simultaneous multi‐slice‐accelerated multi‐shot diffusion weighted imaging
Autor: | Brian K. Rutt, Adam B. Kerr, Baolian Yang, Vincent A. Magnotta, Mathews Jacob, Graeme C. McKinnon, Merry Mani |
---|---|
Rok vydání: | 2019 |
Předmět: |
Speedup
Computer science Phase (waves) FOS: Physical sciences Signal-To-Noise Ratio Regularization (mathematics) Article 030218 nuclear medicine & medical imaging 03 medical and health sciences Acceleration 0302 clinical medicine Image Processing Computer-Assisted Calibration Humans Computer Simulation Radiology Nuclear Medicine and imaging Motion compensation Models Statistical Matrix completion Fourier Analysis Echo-Planar Imaging Phantoms Imaging Brain Reproducibility of Results Signal Processing Computer-Assisted Image Enhancement Physics - Medical Physics Healthy Volunteers Diffusion Magnetic Resonance Imaging Medical Physics (physics.med-ph) Artifacts Joint (audio engineering) Algorithm Algorithms 030217 neurology & neurosurgery |
Zdroj: | Magn Reson Med |
ISSN: | 1522-2594 0740-3194 |
Popis: | PURPOSE: To introduce a novel reconstruction method for simultaneous multi-slice (SMS) accelerated multi-shot diffusion weighted imaging (ms-DWI). METHODS: SMS acceleration using blipped CAIPI schemes have been proposed to speed up the acquisition of ms-DWIs. The reconstruction of the above data requires (i) phase compensation to combine data from different shots and (ii) slice unfolding to separate the data of different slices. The traditional approach is to first estimate the phase maps corresponding to each shot from a navigator or from the slice-aliased individual shot data. The phase maps are subsequently fed to a iterative reconstruction scheme to recover the slice unfolded DWIs. We propose a novel reconstruction method to jointly recover the slice-unfolded k-space data of the multiple shots. The proposed reconstruction is enabled by the low-rank property inherent in the k-space samples of a ms-DW acquisition. Specifically, we recover the missing samples of the multi-shot acquisition by enforcing a low-rank penalty on the block-Hankel matrix formed by the k-space data of each shot for each slice. The joint recovery of the slice-unfolded k-space data is then performed using a SENSE-based slice-unfolding subject to the low-rank constraint. The proposed joint recovery scheme is tested on simulated and in-vivo data and compared to similar un-navigated methods at slice acceleration factors of 2 and 3. RESULTS: Our experiments show effective slice unaliasing and successful recovery of DWIs with minimal phase artifacts using the proposed method. The performance is comparable to existing methods at low acceleration factors and better than existing methods as the acceleration factor increase. CONCLUSION: For the slice acceleration factors considered in this study, the proposed method can successfully recover DWIs from SMS-accelerated ms-DWI acquisitions. |
Databáze: | OpenAIRE |
Externí odkaz: |