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A 3D-UNET for Gibbs artifact removal from quantitative susceptibility maps

Author:Iyad Ba Gari  Shruti Gadewar  Xingyu Wei  Piyush Maiti  Joshua Boyd  Neda Jahanshad  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1767  

Room Session:Concurrent 1  

Institution:Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC  

Adapting the U-net for Multi-coil MRI Reconstruction

Author:Makarand Parigi  Abhinav Saksena  Nicole Seiberlich  Yun Jiang  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1749  

Room Session:Concurrent 1  

Institution:University of Michigan  

ArtifactID: identifying artifacts in low field MRI using deep learning

Author:Marina Manso Jimeno  Keerthi Sravan Ravi  John Thomas Vaughan Jr.  Dotun Oyekunle  Godwin Ogbole  Sairam Geethanath  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1764  

Room Session:Concurrent 1  

Institution:Columbia Magnetic Resonance Research Center (CMRRC)  Columbia University  University College Hospital  

Artificial Intelligence based smart MRI: Towards development of automated workflow for reduction of repeat and reject of scans

Author:PhD, Raghu Prasad  PhD, Harikrishna Rai  Sanket Mali  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1765  

Room Session:Concurrent 1  

Institution:GE Healthcare  

AutoSON: Automated Sequence Optimization by joint training with a Neural network

Author:Hongjun An  Dongmyung Shin  Hyeong-Geol Shin  Woojin Jung  Jongho Lee  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1762  

Room Session:Concurrent 1  

Institution:Seoul National University  

Breath-hold 3D MRCP at 1.5T using Fast 3D mode and a deep learning-based noise-reduction technique

Author:Taku Tajima  Hiroyuki Akai  Koichiro Yasaka  Rintaro Miyo  Masaaki Akahane  Naoki Yoshioka  Shigeru Kiryu  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1775  

Room Session:Concurrent 1  

Institution:International University of Health and Welfare Mita Hospital  International University of Health and Welfare Narita Hospital  The Institute of Medical Science, The University of Tokyo  

Deep J-Sense: An unrolled network for jointly estimating the image and sensitivity maps

Author:Marius Arvinte  Sriram Vishwanath  Ahmed Tewfik  Jonathan Tamir  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1755  

Room Session:Concurrent 1  

Institution:The University of Texas at Austin  

Deep Learning Based Joint MR Image Reconstruction and Under-sampling Pattern Optimization

Author:Vihang Agarwal  Yue Cao  James Balter  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1763  

Room Session:Concurrent 1  

Institution:University of Michigan  

Deep Low-rank plus Sparse Network for Dynamic MR Imaging

Author:Wenqi Huang  Ziwen Ke  Zhuo-Xu Cui  Jing Cheng  Zhilang Qiu  Sen Jia  Yanjie Zhu  Dong Liang  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0225  

Room Session:Concurrent 1  

Institution:Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences  Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences  

Deep, Deep Learning with BART

Author:Moritz Blumenthal  Martin Uecker  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1754  

Room Session:Concurrent 1  

Institution:University Medical Center Göttingen  DZHK (German Centre for Cardiovascular Research)  University of Göttingen  

A Deep-Learning Framework for Image Reconstruction of Undersampled and Motion-Corrupted k-space Data

Author:Nalini Singh  Juan Iglesias  Elfar Adalsteinsson  Adrian Dalca  Polina Golland  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1758  

Room Session:Concurrent 1  

Institution:Massachusetts Institute of Technology  Massachusetts General Hospital  University College London  

DeepSlider: Deep learning-powered gSlider for improved robustness and performance

Author:Juhyung Park  Dongmyung Shin  Hyeong-Geol Shin  Jiye Kim  Jongho Lee  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1759  

Room Session:Concurrent 1  

Institution:Seoul National University  

Design of slice-selective RF pulses using deep learning

Author:Felix Krüger  Max Lutz  Christoph Aigner  Sebastian Schmitter  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0230  

Room Session:Concurrent 1  

Institution:Physikalisch-Technische Bundesanstalt  

Enhancing the Reconstruction quality of Physics-Guided Deep Learning via Holdout Multi-Masking

Author:Burhaneddin Yaman  Seyed Amir Hossein Hosseini  Steen Moeller  Mehmet Akçakaya  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1781  

Room Session:Concurrent 1  

Institution:Center for Magnetic Resonance Research  University of Minnesota  

ENSURE: Ensemble Stein's Unbiased Risk Estimator for Unsupervised Learning

Author:Hemant Kumar Aggarwal  Aniket Pramanik  Mathews Jacob  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1774  

Room Session:Concurrent 1  

Institution:University of Iowa  

Evaluation of Super Resolution Network for Universal Resolution Improvement

Author:Zechen Zhou  Yi Wang  Johannes Peeters  Peter Börnert  Chun Yuan  Marcel Breeuwer  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1777  

Room Session:Concurrent 1  

Institution:MR Clinical Science, Philips Healthcare  MR Clinical Science, Philips Healthcare North America  Philips Research Hamburg  Philips Research North America  Vascular Imaging Lab, University of Washington  

Extending Scan-specific Artifact Reduction in K-space (SPARK) to Advanced Encoding and Reconstruction Schemes

Author:Yamin Arefeen  Onur Beker  Heng Yu  Elfar Adalsteinsson  Berkin Bilgic  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1768  

Room Session:Concurrent 1  

Institution:Athinoula A. Martinos Center for Biomedical Imaging  École Polytechnique Fédérale de Lausanne  Massachusetts Institute of Technology  Tsinghua University  Harvard Medical School  Harvard-MIT Health Sciences and Technology  Institute for Medical Engineering and Science  

Feasibility of Super Resolution Speech RT-MRI using Deep Learning

Author:Prakash Kumar  Yongwan Lim  Krishna Nayak  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1782  

Room Session:Concurrent 1  

Institution:University of Southern California  

Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge

Author:Chompunuch Sarasaen  Soumick Chatterjee  Fatima Saad  Mario Breitkopf  Andreas Nürnberger  Oliver Speck  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1778  

Room Session:Concurrent 1  

Institution:Center for Behavioral Brain Sciences  Otto von Guericke University  Leibniz Institute for Neurobiology  German Center for Neurodegenerative Disease  

Going beyond the image space: undersampled MRI reconstruction directly in the k-space using a complex valued residual neural network

Author:Soumick Chatterjee  Chompunuch Sarasaen  Alessandro Sciarra  Mario Breitkopf  Steffen Oeltze-Jafra  Andreas Nürnberger  Oliver Speck  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1757  

Room Session:Concurrent 1  

Institution:Medical Faculty, University Hopspital  Otto von Guericke University  German Centre for Neurodegenerative Diseases  Center for Behavioral Brain Sciences  Leibniz Institute for Neurobiology  

Higher Resolution with Improved Image Quality without Increased Scan Time: Is it possible with MRI Deep Learning Reconstruction?

Author:Hung Do  Carly Lockard  Dawn Berkeley  Brian Tymkiw  Nathan Dulude  Scott Tashman  Garry Gold  Erin Kelly  Charles Ho  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1776  

Room Session:Concurrent 1  

Institution:Canon Medical Systems USA, Inc.  Stanford University  Steadman Philippon Research Institute  The Steadman Clinic  

Improving Deep Learning MRI Super-Resolution for Quantitative Susceptibility Mapping

Author:Antoine Moevus  Mathieu Dehaes  Benjamin De Leener  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1769  

Room Session:Concurrent 1  

Institution:Polytechnique Montréal  Université de Montréal  Ste-Justine Hospital University Centre  University of Montreal  

Intelligent Incorporation of AI with Model Constraints for MRI Acceleration

Author:Renkuan Zhai  Xiaoqian Huang  Yawei Zhao  Meiling Ji  Xuyang Lv  Mengyao Qian  Shu Liao  Guobin Li  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1760  

Room Session:Concurrent 1  

Institution:United Imaging Healthcare  United Imaging Intelligence  

Joint Data Driven Optimization of MRI Data Sampling and Reconstruction via Variational Information Maximization

Author:Cagan Alkan  Morteza Mardani  Shreyas Vasanawala  John Pauly  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0229  

Room Session:Concurrent 1  

Institution:Stanford University  

Joint Reconstruction of MR Image and Coil Sensitivity Maps using Deep Model-based Network

Author:Yohan Jun  Hyungseob Shin  Taejoon Eo  Dosik Hwang  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0226  

Room Session:Concurrent 1  

Institution:Yonsei University  

Learn to Better Regularize in Constrained Reconstruction

Author:Yue Guan  Yudu Li  Xi Peng  Yao Li  Yiping Du  Zhi-Pei Liang  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1772  

Room Session:Concurrent 1  

Institution:Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign  Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University  Mayo Clinic  Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign  

MAGnitude Image to Complex (MAGIC)-Net: reconstructing multi-coil complex images with pre-trained network using synthesized raw data

Author:Fanwen Wang  Hui Zhang  Jiawei Han  Fei Dai  Yuxiang Dai  Weibo Chen  Chengyan Wang  He Wang  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1753  

Room Session:Concurrent 1  

Institution:Human Phenome Institute, Fudan University  Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University  Philips Healthcare  

A Marriage of Subspace Modeling with Deep Learning to Enable High-Resolution Dynamic Deuterium MR Spectroscopic Imaging

Author:Yudu Li  Yibo Zhao  Rong Guo  Tao Wang  Yi Zhang  Mathew Chrostek  Walter Low  Xiao-Hong Zhu  Wei Chen  Zhi-Pei Liang  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1770  

Room Session:Concurrent 1  

Institution:University of Illinois at Urbana-Champaign  University of Minnesota  

Motion-resolved B1+ prediction using deep learning for real-time pTx pulse-design.

Author:Alix Plumley  Luke Watkins  Kevin Murphy  Emre Kopanoglu  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0223  

Room Session:Concurrent 1  

Institution:Cardiff University Brain Research Imaging Centre  

MRI super-resolution reconstruction: A patient-specific and dataset-free deep learning approach

Author:Yao Sui  Onur Afacan  Ali Gholipour  Simon Warfield  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1779  

Room Session:Concurrent 1  

Institution:Harvard Medical School  Boston Children's Hospital  

MRzero sequence generation using analytic signal equations as forward model and neural network reconstruction for efficient auto-encoding

Author:Simon Weinmüller  Hoai Nam Dang  Alexander Loktyushin  Felix Glang  Arnd Doerfler  Andreas Maier  Bernhard Schölkopf  Klaus Scheffler  Moritz Zaiss  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1761  

Room Session:Concurrent 1  

Institution:Empirical Inference  Friedrich-Alexander Universität Erlangen-Nürnberg (FAU)  Magnetic Resonance Center  Pattern Recognition Lab Friedrich-Alexander-University Erlangen-Nürnberg  Eberhard Karls University Tübingen  

Multi-channel and multi-group-based CNN Image Reconstruction using Equal-sized Multi-resolution Image Decomposition

Author:Shohei Ouchi  Satoshi ITO  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1750  

Room Session:Concurrent 1  

Institution:Utsunomiya University  

Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising using Limited Data

Author:Arjun Desai  Batu Ozturkler  Christopher Sandino  Brian Hargreaves  John Pauly  Akshay Chaudhari  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1773  

Room Session:Concurrent 1  

Institution:Stanford University  

On Instabilities of Conventional Multi-Coil MRI Reconstruction To Small Adversarial Perturbations

Author:Chi Zhang  Jinghan Jia  Burhaneddin Yaman  Steen Moeller  Sijia Liu  Mingyi Hong  Mehmet Akçakaya  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0221  

Room Session:Concurrent 1  

Institution:IBM Research  University of Florida  University of Minnesota  

Optical Flow-based Data Augmentation and its Application in Deep Learning Super Resolution

Author:Yu He  Fangfang Tang  Jin Jin  Feng Liu  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1783  

Room Session:Concurrent 1  

Institution:The University of Queensland  Siemens Healthcare  

PCA and U-Net based Channel Compression for Fast MR Image Reconstruction

Author:Madiha Arshad  Mahmood Qureshi  Omair Inam  Hammad Omer  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1752  

Room Session:Concurrent 1  

Institution:COMSATS University  

Removing structured noise from dynamic arterial spin labeling images

Author:Yanchen Guo  Zongpai Zhang  Shichun Chen  Lijun Yin  David Alsop  Weiying Dai  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1771  

Room Session:Concurrent 1  

Institution:Beth Israel Deaconess Medical Center & Harvard Medical School  State University of New York at Binghamton  

Rethinking complex image reconstruction: ?-loss for improved complex image reconstruction with deep learning

Author:Maarten Terpstra  Matteo Maspero  Jan Lagendijk  Cornelis van den Berg  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1751  

Room Session:Concurrent 1  

Institution:University Medical Center Utrecht  

Robust Multi-shot EPI with Untrained Artificial Neural Networks: Unsupervised Scan-specific Deep Learning for Blip Up-Down Acquisition (BUDA)

Author:Tae Hyung Kim  Zijing Zhang  Jaejin Cho  Borjan Gagoski  Justin Haldar  Berkin Bilgic  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0224  

Room Session:Concurrent 1  

Institution:Athinoula A. Martinos Center for Biomedical Imaging  Boston Children's Hospital  University of Southern California  Harvard Medical School  Zhejiang University  

An self-supervised deep learning based super-resolution method for quantitative MRI

Author:Muzi Guo  Yuanyuan Liu  Yuxin Yang  Dong Liang  Hairong Zheng  Yanjie Zhu  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1780  

Room Session:Concurrent 1  

Institution:Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences  University of Chinese Academy of Sciences  

Subtle Inverse Crimes: Naively using Publicly Available Images Could Make Reconstruction Results Seem Misleadingly Better!

Author:Efrat Shimron  Jonathan Tamir  Ke Wang  Michael Lustig  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0222  

Room Session:Concurrent 1  

Institution:The University of Texas at Austin  UC Berkeley  

Uncertainty estimation for DL-based motion artifact correction in 3D brain MRI

Author:Karsten Sommer  Jochen Keupp  Christophe Schuelke  Oliver Lips  Tim Nielsen  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning: Removing Artifacts & Improving Resolution  

Program Number:1766  

Room Session:Concurrent 1  

Institution:Philips Research  

Ungated time-resolved cardiac MRI with temporal subspace constraint using SSA-FARY SE

Author:Sebastian Rosenzweig  Martin Uecker  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0227  

Room Session:Concurrent 1  

Institution:University Medical Center Göttingen  German Centre for Cardiovascular Research (DZHK)  

A unified model for simultaneous reconstruction and R2* mapping of accelerated 7T data using the Recurrent Inference Machine

Author:Chaoping Zhang  Dirk Poot  Bram Coolen  Hugo Vrenken  Pierre-Louis Bazin  Birte Forstmann  Matthan Caan  

Session Type:Oral  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:0228  

Room Session:Concurrent 1  

Institution:Amsterdam UMC  Erasmus MC  University of Amsterdam  Max Planck Institute for Human Cognitive and Brain Sciences  

Using data-driven image priors for image reconstruction with BART

Author:Guanxiong Luo  Moritz Blumenthal  Martin Uecker  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Data Acquisition & Image Reconstruction  

Session Name:Machine Learning for Data Acquisition & Image Reconstruction  

Program Number:1756  

Room Session:Concurrent 1  

Institution:University Medical Center Göttingen, Germany  University of Göttingen, Germany