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Abstract #4269

Acceleration of multi-echo high resolution brain imaging using variable-density sampling and patch-based regularization framework

Jyoti Mangal1,2, Donovan Tripp1, Rene Botnar1,3,4, Claudia Prieto1,3,4, and David W Carmichael1,2
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2London Collaborative Ultra high field System (LoCUS), London, United Kingdom, 3School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 4Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

Synopsis

Keywords: Image Reconstruction, High-Field MRI

Motivation: Long acquisition times facilitate the acquisition of high resolution multiparametric maps at 7T, however long scan times can lead to motion artefacts even with accelerated k-space sampling.

Goal(s): Our goal is to reduce acquisition time and reduce motion artefacts using variable-density sampling.

Approach: We use the variable-density-cartesian-trajectory (VD-CASPR) to retrospectively undersample the k-space of fully-sampled multi-echo GRE data in spiral-like interleaves for acceleration factors 6, 8 and 10. HDPROST regularisation framework is used to reduce motion artefacts taking advantage of the multiple echoes by patch-based denoising.

Results: HDPROST enables greater acceleration potential taking avantage of the information redundancy and incoherent aliasing across echoes.

Impact: This work demonstrates a reconstruction technique that may allow for faster high-resolution quantitative mapping which may be beneficial for a range of neurological applications, especially in the identification and characterization of small scale brain architecture and its alteration in pathology.

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Keywords