Print Email Facebook Twitter Learning-based method for k-space trajectory design in MRI Title Learning-based method for k-space trajectory design in MRI Author Sharma, Shubham (Indian Institute of Science) Hari, K.V.S. (Indian Institute of Science) Leus, G.J.T. (TU Delft Signal Processing Systems) Date 2022 Abstract Variable density sampling of the k-space in MRI is an integral part of trajectory design. It has been observed that data-driven trajectory design methods provide a better image reconstruction as compared to trajectories obtained from a fixed or a parametric density function. In this paper, a data-driven strategy has been proposed to obtain non-Cartesian continuous k-space sampling trajectories for MRI under the compressed sensing framework (greedy non-Cartesian (GNC)). A stochas-tic version of the algorithm (stochastic greedy non-Cartesian (SGNC)) is also proposed that reduces the computation time. We compare the proposed trajectory with a traveling salesman problem (TSP)-based trajectory and an echo planar imaging-like trajectory obtained by a greedy method called stochastic greedy-Cartesian (SGC) algorithm. The training images are taken from knee images of the fastMRI dataset. It is observed that the proposed algorithms outperform the TSP-based and the SGC trajectories for similar read-out times. Subject MRIvariable-density samplindata-drivenk-space trajectory design To reference this document use: http://resolver.tudelft.nl/uuid:8375af69-7ca4-47d8-b7f6-4f002ee3755d DOI https://doi.org/10.1109/EMBC48229.2022.9871692 Publisher IEEE Embargo date 2023-03-08 ISBN 978-1-7281-2783-5 Source Proceedings of the 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Event 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022-07-11 → 2022-07-15, Glasgow, United Kingdom Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type conference paper Rights © 2022 Shubham Sharma, K.V.S. Hari, G.J.T. Leus Files PDF Learning_based_method_for ... in_MRI.pdf 2.6 MB Close viewer /islandora/object/uuid:8375af69-7ca4-47d8-b7f6-4f002ee3755d/datastream/OBJ/view