Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction

• URL: http://arxiv.org/abs/2007.05993v1
• Date: Sun, 12 Jul 2020 13:58:07 GMT
• Title: Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction
• Authors: Chen Qin, Jo Schlemper, Kerstin Hammernik, Jinming Duan, Ronald M Summers, and Daniel Rueckert
• Abstract summary: We present a deep network strategy for accelerated parallel MR image reconstruction. In particular, we examine the network in parameter space between a source model that is formulated in an unroll scheme with L1 and SSIM losses and its counterpart that is trained with an adversarial loss.
• Score: 14.151673559127753
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a deep network interpolation strategy for accelerated parallel MR image reconstruction. In particular, we examine the network interpolation in parameter space between a source model that is formulated in an unrolled scheme with L1 and SSIM losses and its counterpart that is trained with an adversarial loss. We show that by interpolating between the two different models of the same network structure, the new interpolated network can model a trade-off between perceptual quality and fidelity.

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