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04/17/2022
Accelerated MRI With Deep Linear Convolutional Transform Learning
Recent studies show that deep learning (DL) based MRI reconstruction out...
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03/23/2022
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging
Physics-driven deep learning methods have emerged as a powerful tool for...
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05/17/2021
Unsupervised Deep Learning Methods for Biological Image Reconstruction
Recently, deep learning approaches have become the main research frontie...
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05/12/2021
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction
High spatial and temporal resolution across the whole brain is essential...
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05/10/2021
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning
Functional MRI (fMRI) is commonly used for interpreting neural activitie...
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02/25/2021
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations
Although deep learning (DL) has received much attention in accelerated M...
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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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11/18/2020
Self-Supervised Physics-Guided Deep Learning Reconstruction For High-Resolution 3D LGE CMR
Late gadolinium enhancement (LGE) cardiac MRI (CMR) is the clinical stan...
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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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04/29/2020
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset
Purpose: To organize a knee MRI segmentation challenge for characterizin...
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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
Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data
Deep learning (DL) has emerged as a tool for improving accelerated MRI r...
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04/01/2019
