Compressed sensing MRI reconstruction from 3D multichannel data using GPUs
Sign Up to like & getrecommendations! Published in 2017 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.26636
Abstract: To accelerate iterative reconstructions of compressed sensing (CS) MRI from 3D multichannel data using graphics processing units (GPUs). read more here.
Keywords: data using; compressed sensing; mri reconstruction; multichannel data ... See more keywords
Analysis of deep complex‐valued convolutional neural networks for MRI reconstruction and phase‐focused applications
Sign Up to like & getrecommendations! Published in 2021 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.28733
Abstract: Deep learning has had success with MRI reconstruction, but previously published works use real‐valued networks. The few works which have tried complex‐valued networks have not fully assessed their impact on phase. Therefore, the purpose of… read more here.
Keywords: phase; convolutional neural; mri reconstruction; valued convolutional ... See more keywords
Bayesian MRI reconstruction with joint uncertainty estimation using diffusion models
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DOI: 10.1002/mrm.29624
Abstract: We introduce a framework that enables efficient sampling from learned probability distributions for MRI reconstruction. read more here.
Keywords: bayesian mri; reconstruction joint; reconstruction; joint uncertainty ... See more keywords
CS-MRI reconstruction via group-based eigenvalue decomposition and estimation
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.12.038
Abstract: Abstract This paper proposes a novel method for compressed sensing MRI (CS-MRI) reconstruction that combines both the sparse representation and statistical estimation. In this work, the low-rank property is observed and utilized to sparsely represent… read more here.
Keywords: reconstruction; estimation; mri reconstruction; group based ... See more keywords
An Effective Co-Support Guided Analysis Model for Multi-Contrast MRI Reconstruction
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2023.3244669
Abstract: Multi-contrast magnetic resonance imaging (MRI) is widely used in clinical diagnosis. However, it is time-consuming to obtain MR data of multi-contrasts and the long scanning time may bring unexpected physiological motion artifacts. To obtain MR… read more here.
Keywords: contrast; multi contrast; support; model ... See more keywords
High-Fidelity MRI Reconstruction Using Adaptive Spatial Attention Selection and Deep Data Consistency Prior
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2023.3258839
Abstract: Compressed sensing (CS) has shown great potential for fast magnetic resonance imaging (fastMRI). Traditional CS methods model the inverse problem by leveraging the sparsity prior to guarantee the success of signal recovery, which is not… read more here.
Keywords: high fidelity; fidelity mri; data consistency; consistency prior ... See more keywords
TRANS-Net: Transformer-Enhanced Residual-Error AlterNative Suppression Network for MRI Reconstruction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3205684
Abstract: Since deep priors could exploit more intrinsic features than handcrafted prior knowledge, unrolled reconstruction methods significantly improve image quality for fast magnetic resonance imaging (MRI) reconstruction with the combination of iterative optimization and deep neural… read more here.
Keywords: network; trans net; error; reconstruction ... See more keywords
Improved Computational Efficiency of Locally Low Rank MRI Reconstruction Using Iterative Random Patch Adjustments
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2017.2659742
Abstract: This paper presents and analyzes an alternative formulation of the locally low-rank (LLR) regularization framework for magnetic resonance image (MRI) reconstruction. Generally, LLR-based MRI reconstruction techniques operate by dividing the underlying image into a collection… read more here.
Keywords: regularization; low rank; mri reconstruction; llr regularization ... See more keywords
Uncertainty Quantification in Deep MRI Reconstruction
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2020.3025065
Abstract: Reliable MRI is crucial for accurate interpretation in therapeutic and diagnostic tasks. However, undersampling during MRI acquisition as well as the overparameterized and non-transparent nature of deep learning (DL) leaves substantial uncertainty about the accuracy… read more here.
Keywords: reconstruction; mri reconstruction; uncertainty; quantification deep ... See more keywords
NC-PDNet: A Density-Compensated Unrolled Network for 2D and 3D Non-Cartesian MRI Reconstruction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2022.3144619
Abstract: Deep Learning has become a very promising avenue for magnetic resonance image (MRI) reconstruction. In this work, we explore the potential of unrolled networks for non-Cartesian acquisition settings. We design the NC-PDNet (Non-Cartesian Primal Dual… read more here.
Keywords: network; pdnet; mri reconstruction; density compensated ... See more keywords
Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2022.3147426
Abstract: Supervised reconstruction models are characteristically trained on matched pairs of undersampled and fully-sampled data to capture an MRI prior, along with supervision regarding the imaging operator to enforce data consistency. To reduce supervision requirements, the… read more here.
Keywords: reconstruction; mri reconstruction; zero shot; unsupervised mri ... See more keywords