Magnetic Resonance Imaging

A common limitation of MRI are the comparably long measurement times. In this project, we aim to address this problem by developing sophisticated image reconstruction methods taking into account our prior knowledge about the expected structure of MRI images. Moreover, we are interested in the development of robust reconstruction methods that take into account system imperfections such as the inhomogeneity of the main magnetic field. For fast imaging sequences with long readouts, neglecting such imperfections leads to visible artifacts corrupting the image. Incorporating imperfections into the reconstruction thus opens up the door to use fast imaging sequences and thus allows to reduce the scan time or improve the resolution.

Artifacts from a single-shot spiral MRI acquisition can be mitigated by taking into account the inhomogeneity of the main magnetic field during image reconstruction.

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Project Publications

  • M. Grosser and T. Knopp (2021). Fast Image Reconstruction for Non-Cartesian Acquisitions in the Presence of B0-inhomogeneities. Proc. ISMRM 2021.

  • M. Grosser and T. Knopp (2020). Accelerated Multi-Echo Gradient Echo Imaging using Locally-Low Rank Regularization. Proc. ISMRM 2020.

  • M. Grosser, T. Knopp (2021). Efficient Optimization Of MRI Sampling Patterns Using The Bayesian Fisher Information Matrix. IEEE 18th International Symposium on Biomedical Imaging (ISBI). 234-237

  • T. Knopp and M. Grosser (2021). MRIReco.jl: An MRI Reconstruction Framework written in Julia. Magn. Reson. Med.. 86. (3), 1633-1646 [doi] [www]

  • T. Knopp and M. Grosser (2019). MRIReco.jl: An Extensible Open-Source Image Reconstruction Framework written in Julia. Proc. ISMRM 2019.