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08/05/2023
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets
Although deep learning (DL) methods are powerful for solving inverse pro...
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12/21/2022
High-fidelity Direct Contrast Synthesis from Magnetic Resonance Fingerprinting
Magnetic Resonance Fingerprinting (MRF) is an efficient quantitative MRI...
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09/16/2021
Subtle Inverse Crimes: Naïvely training machine learning algorithms could lead to overly-optimistic results
While open databases are an important resource in the Deep Learning (DL)...
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08/27/2021
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss
Purpose: To improve reconstruction fidelity of fine structures and textu...
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03/06/2021
Memory-efficient Learning for High-Dimensional MRI Reconstruction
Deep learning (DL) based unrolled reconstructions have shown state-of-th...
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05/27/2020
How to do Physics-based Learning
The goal of this tutorial is to explain step-by-step how to implement ph...
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12/11/2019
Memory-efficient Learning for Large-scale Computational Imaging
Computational imaging systems jointly design computation and hardware to...
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09/11/2018
Clinically Deployed Distributed Magnetic Resonance Imaging Reconstruction: Application to Pediatric Knee Imaging
Magnetic resonance imaging is capable of producing volumetric images wit...
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08/10/2018
Physics-based Learned Design: Optimized Coded-Illumination for Quantitative Phase Imaging
Coded-illumination based reconstruction of Quantitative Phase (QP) is ge...
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09/15/2017
General Phase Regularized Reconstruction using Phase Cycling
Purpose: To develop a general phase regularized image reconstruction met...
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07/01/2017
Better than Real: Complex-valued Neural Nets for MRI Fingerprinting
The task of MRI fingerprinting is to identify tissue parameters from com...
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10/03/2016
On the Empirical Effect of Gaussian Noise in Under-sampled MRI Reconstruction
In Fourier-based medical imaging, sampling below the Nyquist rate result...
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07/17/2015