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02/15/2021
Scan-Specific MRI Reconstruction using Zero-Shot Physics-Guided Deep Learning
Physics-guided deep learning (PG-DL) has emerged as a powerful tool for ...
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10/26/2020
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking
Physics-guided deep learning (PG-DL) via algorithm unrolling has receive...
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08/13/2020
Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI
Purpose: To develop an improved self-supervised learning strategy that e...
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06/16/2020
Noise2Inpaint: Learning Referenceless Denoising by Inpainting Unrolling
Deep learning based image denoising methods have been recently popular d...
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05/12/2020
High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks
Long scan duration remains a challenge for high-resolution MRI. Deep lea...
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12/16/2019
Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data
Purpose: To develop a strategy for training a physics-driven MRI reconst...
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12/16/2019
Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms
Inverse problems in medical imaging applications incorporate domain-spec...
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10/21/2019
