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Extending LOUPE for K-space Under-sampling Pattern Optimization in Multi-coil MRI [article]

Jinwei Zhang, Hang Zhang, Alan Wang, Qihao Zhang, Mert Sabuncu, Pascal Spincemaille, Thanh D. Nguyen, Yi Wang
2020 arXiv   pre-print
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]

Jinwei Zhang, Hang Zhang, Chao Li, Pascal Spincemaille, Mert Sabuncu, Thanh D. Nguyen, Yi Wang
2021 arXiv   pre-print
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]

Cagla Deniz Bahadir, Adrian V. Dalca, Mert R. Sabuncu
2019 Lecture Notes in Computer Science  
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]

Chaithya G R
2021 arXiv   pre-print
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]

Junwei Yang, Xiao-Xin Li, Feihong Liu, Dong Nie, Pietro Lio, Haikun Qi, Dinggang Shen
2021 arXiv   pre-print
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]

Marcelo V. W. Zibetti, Florian Knoll, Ravinder R. Regatte
2021 arXiv   pre-print
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]

Cagla D. Bahadir, Alan Q. Wang, Adrian V. Dalca, Mert R. Sabuncu
2020 arXiv   pre-print
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]

Zhishen Huang, Saiprasad Ravishankar
2022 arXiv   pre-print
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]

Hemant Kumar Aggarwal, Mathews Jacob
2020 arXiv   pre-print
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]

Yiming Liu, Yanwei Pang, Ruiqi Jin, Zhenchang Wang
2022 arXiv   pre-print
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

G R Chaithya, Zaccharie Ramzi, Philippe Ciuciu
2021 2021 29th European Signal Processing Conference (EUSIPCO)   unpublished
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  
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)

Stefano Selleri
2017 Radio Science Bulletin  
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  
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  
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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