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Extending LOUPE for K-space Under-sampling Pattern Optimization in Multi-coil MRI
[article]
2020
arXiv
pre-print
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The previously established LOUPE (Learning-based Optimization of the Under-sampling Pattern) framework for optimizing the k-space sampling pattern in MRI was extended in three folds: firstly, fully sampled ...
multi-coil k-space data from the scanner, rather than simulated k-space data from magnitude MR images in LOUPE, was retrospectively under-sampled to optimize the under-sampling pattern of in-vivo k-space ...
Conclusions In this work, LOUPE for optimizing the k-space sampling pattern in MRI was extended by training on in-vivo multi-coil k-space data and using the unrolled network for under-sampled reconstruction ...
arXiv:2007.14450v1
fatcat:mkwqlddxg5b77geht6io3fulkm
Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction
[article]
2021
arXiv
pre-print
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A multi-echo sampling pattern optimization block extended from LOUPE-ST is proposed to optimize the k-space sampling patterns along echoes. ...
method in MRI. ...
Deep ADMM (a) was used as backbone for undersampled k-p space reconstruction. A sampling pattern optimization block (b) extended from LOUPE-ST was used to learn optimal multi-echo patterns. ...
arXiv:2103.05878v1
fatcat:paisyy3tzvhwrpibrocpfl34fq
Learning-Based Optimization of the Under-Sampling Pattern in MRI
[chapter]
2019
Lecture Notes in Computer Science
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The long scan times of Magnetic Resonance Imaging (MRI) create a bottleneck in patient care and acquisitions can be accelerated by under-sampling in k-space (i.e., the Fourier domain). ...
In this thesis, we focus on the optimization of the sub-sampling pattern with a data-driven framework. ...
We call our algorithm LOUPE, which stands for Learning-based Optimization of the Under-sampling Pattern. ...
doi:10.1007/978-3-030-20351-1_61
fatcat:vy6ojeq3d5bwjnct4s3bertk3a
Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction
[article]
2021
arXiv
pre-print
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The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. ...
Recently, datadriven learning schemes such as LOUPE have been proposed to learn a discrete sampling pattern, by jointly optimizing the whole pipeline from data acquisition to image reconstruction. ...
ACKNOWLEDGMENTS We acknowledge the French Institute of development and resources in scientific computing for their AI program allowing us to use the Jean Zay supercomputer's GPU partitions. ...
arXiv:2103.03559v2
fatcat:qpu53wwguzaufhr6q67rgxtecy
Fast T2w/FLAIR MRI Acquisition by Optimal Sampling of Information Complementary to Pre-acquired T1w MRI
[article]
2021
arXiv
pre-print
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To this end, we propose an iterative framework to optimize the under-sampling pattern for MRI acquisition of another modality that can complement the fully-sampled T1-weighted MR image at different under-sampling ...
image in improving the MRI reconstruction. ...
Under-sampling Pattern Learning The under-sampling pattern used in k-space plays an important role in MRI reconstruction. ...
arXiv:2111.06400v1
fatcat:wx76xl5ykjdizfzoeaeocbzqem
Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications
[article]
2021
arXiv
pre-print
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Purpose: To propose an alternating learning approach to learn the sampling pattern (SP) and the parameters of variational networks (VN) in accelerated parallel magnetic resonance imaging (MRI). ...
The algorithm learns an effective pair: an SP that captures fewer k-space samples generating undersampling artifacts that are removed by the VN reconstruction. ...
and extended in [48] for multi-coil, or parallel, MRI. ...
arXiv:2110.14703v1
fatcat:2oa6j3c2bva2jgpixf57lfd53i
Deep-learning-based Optimization of the Under-sampling Pattern in MRI
[article]
2020
arXiv
pre-print
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In compressed sensing MRI (CS-MRI), k-space measurements are under-sampled to achieve accelerated scan times. ...
Our experiments also show how LOUPE yielded optimal under-sampling patterns that were significantly different for brain vs knee MRI scans. ...
DATA-DRIVEN UNDER-SAMPLING IN COMPRESSED SENSING MRI The under-sampling pattern in k-space is closely related to reconstruction performance. ...
arXiv:1907.11374v3
fatcat:gahgolokgrdexd7jyqi4hshvuu
Single-pass Object-adaptive Data Undersampling and Reconstruction for MRI
[article]
2022
arXiv
pre-print
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The network observes very limited low-frequency k-space data for each object and rapidly predicts the desired undersampling pattern in one go that achieves high image reconstruction quality. ...
The source code for the proposed joint sampling and reconstruction learning framework is available at https://github.com/zhishenhuang/mri. ...
We thank all reviewers for their constructive comments on our initial draft. ...
arXiv:2111.09212v2
fatcat:ikmkfv2hfrcathmkhryqymvjh4
J-MoDL: Joint Model-Based Deep Learning for Optimized Sampling and Reconstruction
[article]
2020
arXiv
pre-print
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The image quality of these approaches is heavily dependent on the sampling pattern. We introduce a continuous strategy to jointly optimize the sampling pattern and network parameters. ...
This approach facilitates the joint and continuous optimization of the sampling pattern and the CNN parameters to improve image quality. ...
Instead of directly solving for the k-space locations, the LOUPE approach optimizes for the sampling density [35] . ...
arXiv:1911.02945v3
fatcat:bmswtqy2gvaejoueduowvyvv4y
Active Phase-Encode Selection for Slice-Specific Fast MR Scanning Using a Transformer-Based Deep Reinforcement Learning Framework
[article]
2022
arXiv
pre-print
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Purpose: Long scan time in phase encoding for forming complete K-space matrices is a critical drawback of MRI, making patients uncomfortable and wasting important time for diagnosing emergent diseases. ...
K-space matrix. ...
Jinghua Wang for calculating the maximum of allowable phase selection and correcting typos of the manuscript. ...
arXiv:2203.05756v1
fatcat:druryj2lgjdfrlgn63xadvg2f4
Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction
2021
2021 29th European Signal Processing Conference (EUSIPCO)
unpublished
Preserved Fulltext
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The file type is application/pdf.
The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. ...
Recently, data-driven learning schemes such as LOUPE have been proposed to learn a discrete sampling pattern, by jointly optimizing the whole pipeline from data acquisition to image reconstruction. ...
ACKNOWLEDGMENTS We acknowledge the French Institute of development and resources in scientific computing for their AI program allowing us to use the Jean Zay supercomputer's GPU partitions. ...
doi:10.23919/eusipco54536.2021.9616336
fatcat:yu4po6k3unbv3kxp3bndbqjucm
40th Meeting of the Canadian Congress of Neurological Sciences
2005
Canadian Journal of Neurological Sciences
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subarachnoid space. ...
In each case, microsurgery was performed under multi-modality intra-operative neurophysiological monitoring. The most common complications encountered were CSF leak and infections. ...
Discontinuation due to adverse events in ESPS-2 was 27.8% for AGGRENOX, 28.2% for extended release dipyridamole, 23.2% for ASA, and 23.7% for placebo. ...
doi:10.1017/s0317167100003310
fatcat:7cedlythjvcf3lbsol3ugogfy4
Claude Chappe and the first telecommunication network (without electricity)
2017
Radio Science Bulletin
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This study was supported by the Russian Foundation for Basic Research (grant no. ...
Acknowledgments The author very much thanks the anonymous reviewers for their comments, which helped to make the text clearer. ...
The 40th anniversary of Franco-Russian space cooperation: Russian Cosmonauts posing with Jean-Loup Chrétien.
Figure 8 . 8 Figure 8. ...
doi:10.23919/ursirsb.2017.8113174
fatcat:xz27ckavmbajfefnxzvkzjywba
Oral Presentations
2017
Global Spine Journal
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We thank Eva Roth for her help in IVD isolation and biomechanical assays. ...
Acknowledgements We thank Eva Roth for her help in IVD isolation and biomechanical assays. ...
Conclusions: In conclusion, K-MRI adds the benefits of MRI to those of a dynamic study, allowing the diagnosis of otherwise unidentifiable situations, gaining a more and more important role in cervical ...
doi:10.1177/2192568217708577
fatcat:xa6fqbninffwvpdylyble6wo74
29th Meeting of the Canadian Congress of Neurological Sciences
1994
Canadian Journal of Neurological Sciences
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The diagnostic success of a stereotactic biopsy probably depends largely on the histological nature of the lesion, and the optimal targetting and sampling of the lesion. ...
Alterations in the Normal Pattern of Cervical Spinal Cord Motion as Measured by MRI in Selected Pathologic States
D.J. ...
Some had MRI abnormalities and this lead to the diagnosis of multiple sclerosis in 2. Diagnosis was suspected by ELISA (HTLV-1/2 positivity, CDC). ...
doi:10.1017/s0317167100040804
fatcat:ikytez2fg5ft5cpvwxgwtsi5de
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