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End-to-End Sequential Sampling and Reconstruction for MR Imaging

Yin, Tianwei and Wu, Zihui and Sun, He and Dalca, Adrian V. and Yue, Yisong and Bouman, Katherine L. (2021) End-to-End Sequential Sampling and Reconstruction for MR Imaging. . (Unpublished)

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Accelerated MRI shortens acquisition time by subsampling in the measurement k-space. Recovering a high-fidelity anatomical image from subsampled measurements requires close cooperation between two components: (1) a sampler that chooses the subsampling pattern and (2) a reconstructor that recovers images from incomplete measurements. In this paper, we leverage the sequential nature of MRI measurements, and propose a fully differentiable framework that jointly learns a sequential sampling policy simultaneously with a reconstruction strategy. This co-designed framework is able to adapt during acquisition in order to capture the most informative measurements for a particular target (Figure 1). Experimental results on the fastMRI knee dataset demonstrate that the proposed approach successfully utilizes intermediate information during the sampling process to boost reconstruction performance. In particular, our proposed method outperforms the current state-of-the-art learned k-space sampling baseline on up to 96.96% of test samples. We also investigate the individual and collective benefits of the sequential sampling and co-design strategies. Code and more visualizations are available at this http URL []

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemCode and supplementary materials
Sun, He0000-0003-1526-6787
Dalca, Adrian V.0000-0002-8422-0136
Yue, Yisong0000-0001-9127-1989
Bouman, Katherine L.0000-0003-0077-4367
Additional Information:Code and supplementary materials are available at this http URL
Group:Astronomy Department
Record Number:CaltechAUTHORS:20210604-142545306
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109396
Deposited By: George Porter
Deposited On:07 Jun 2021 14:21
Last Modified:07 Jun 2021 14:21

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