Multi PILOT: Learned Feasible Multiple Acquisition Trajectories for Dynamic MRI

• URL: http://arxiv.org/abs/2303.07150v2
• Date: Thu, 23 Mar 2023 12:49:39 GMT
• Title: Multi PILOT: Learned Feasible Multiple Acquisition Trajectories for Dynamic MRI
• Authors: Tamir Shor, Tomer Weiss, Dor Noti, Alex Bronstein
• Abstract summary: In this study, we consider acquisition learning in the dynamic imaging setting. We design an end-to-end pipeline for the joint optimization of multiple per-frame acquisition trajectories. We demonstrate improved image reconstruction quality in shorter acquisition times.
• Score: 0.7843343739054056
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Dynamic Magnetic Resonance Imaging (MRI) is known to be a powerful and reliable technique for the dynamic imaging of internal organs and tissues, making it a leading diagnostic tool. A major difficulty in using MRI in this setting is the relatively long acquisition time (and, hence, increased cost) required for imaging in high spatio-temporal resolution, leading to the appearance of related motion artifacts and decrease in resolution. Compressed Sensing (CS) techniques have become a common tool to reduce MRI acquisition time by subsampling images in the k-space according to some acquisition trajectory. Several studies have particularly focused on applying deep learning techniques to learn these acquisition trajectories in order to attain better image reconstruction, rather than using some predefined set of trajectories. To the best of our knowledge, learning acquisition trajectories has been only explored in the context of static MRI. In this study, we consider acquisition trajectory learning in the dynamic imaging setting. We design an end-to-end pipeline for the joint optimization of multiple per-frame acquisition trajectories along with a reconstruction neural network, and demonstrate improved image reconstruction quality in shorter acquisition times. The code for reproducing all experiments is accessible at https://github.com/tamirshor7/MultiPILOT.

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