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Magnetic resonance imaging (MRI) is a cornerstone of modern medical imaging.
The dicom standard
Charles Parisot · 1995
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Sense: sensitivity encoding for fast mri
Klaas P Pruessmann, Markus Weiger, Markus B Scheidegger, and Peter Boesiger · 1999
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Introduction to the dicom standard
Peter Mildenberger, Marco Eichelberg, and Eric Martin · 2002
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Dynamic load at baseline can predict radiographic disease progression in medial compartment knee osteoarthritis
T Miyazaki, M Wada, H Kawahara, M Sato, H Baba, and S Shimada · 2002
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T2 relaxation time of cartilage at mr imaging: comparison with severity of knee osteoarthritis
Timothy C Dunn, Ying Lu, Hua Jin, Michael D Ries, and Sharmila Majumdar · 2004
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Potential strategies to reduce medial compartment loading in patients with knee osteoarthritis of varying severity: reduced walking speed
Anne Mündermann, Chris O Dyrby, Debra E Hurwitz, Leena Sharma, and Thomas P Andriacchi · 2004
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A complete distortion correction for MR images: I. gradient warp correction
Simon J Doran, Liz Charles-Edwards, Stefan A Reinsberg, and Martin O Leach · 2005
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Joint image reconstruction and sensitivity estimation in sense (jsense)
Leslie Ying and Jinhua Sheng · 2007
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The osteoarthritis initiative: report on the design rationale for the magnetic resonance imaging protocol for the knee
C.G. Peterfy, E. Schneider, and M. Nevitt · 2008
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Alzheimer's disease neuroimaging initiative (ADNI): Clinical characterization
R. C. Petersen, P. S. Aisen, L. A. Beckett, M. C. Donohue, A. C. Gamst, D. J. Harvey, C. R. Jack, W. J. Jagust, L. M. Shaw, A. W. Toga, J. Q. Trojanowski, and M. W. Weiner · 2009
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Segmentation of knee images: a grand challenge
Tobias Heimann, Bryan J Morrison, Martin A Styner, Marc Niethammer, and S Warfield · 2010
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Evolution of semi-quantitative whole joint assessment of knee OA: MOAKS (MRI osteoarthritis knee score)
D.J. Hunter, A. Guermazi, G.H. Lo, A.J. Grainger, P.G. Conaghan, R.M. Boudreau, and F.W. Roemer · 2011
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Cartilage and meniscal t2 relaxation time as non-invasive biomarker for knee osteoarthritis and cartilage repair procedures
T. Baum, G.B. Joseph, D.C. Karampinos, P.M. Jungmann, T.M. Link, and J.S. Bauer · 2013
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Creation of fully sampled mr data repository for compressed sensing of the knee
K Epperson · 2013
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Association of knee injuries with accelerated knee osteoarthritis progression: Data from the osteoarthritis initiative
Jeffrey B. Driban, Charles B. Eaton, Grace H. Lo, Robert J. Ward, Bing Lu, and Timothy E. McAlindon · 2014
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Interactive whole-heart segmentation in congenital heart disease
Danielle F. Pace, Adrian V. Dalca, Tal Geva, Andrew J. Powell, Mehdi H. Moghari, and Polina Golland · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Cited alongside, same era.
Data from prostate-mri, 2016
Peter Choyke, Baris Turkbey, Peter Pinto, Maria Merino, and Brad Wood · 2016
Cited alongside, same era.
Multimodal population brain imaging in the UK biobank prospective epidemiological study
Karla L Miller, Fidel Alfaro-Almagro, Neal K Bangerter, David L Thomas, Essa Yacoub, Junqian Xu, Andreas J Bartsch, Saad Jbabdi, Stamatios N Sotiropoulos, Jesper L R Andersson, Ludovica Griffanti, Gwenaëlle Douaud, Thomas W Okell, Peter Weale, Iulius Dragonu, Steve Garratt, Sarah Hudson, Rory Collins, Mark Jenkinson, Paul M Matthews, and Stephen M Smith · 2016
Cited alongside, same era.
V-net: Fully convolutional neural networks for volumetric medical image segmentation
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016
Cited alongside, same era.
Five-minute knee MRI for simultaneous morphometry and t2 relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3t
Akshay S. Chaudhari, Marianne S. Black, Susanne Eijgenraam, Wolfgang Wirth, Susanne Maschek, Bragi Sveinsson, Felix Eckstein, Edwin H.G. Oei, Garry E. Gold, and Brian A. Hargreaves · 2017
Dosma: A deep-learning, open-source framework for musculoskeletal mri analysis
Arjun D Desai, Marco Barbieri, Valentina Mazzoli, Elka Rubin, Marianne S Black, Lauren E Watkins, Garry E Gold, Brian A Hargreaves, and Akshay S Chaudhari · 2019
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Technical considerations for semantic segmentation in mri using convolutional neural networks
Arjun D Desai, Garry E Gold, Brian A Hargreaves, and Akshay S Chaudhari · 2019
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Time-saving opportunities in knee osteoarthritis: T2 mapping and structural imaging of the knee using a single 5-min MRI scan
Susanne M. Eijgenraam, Akshay S. Chaudhari, Max Reijman, Sita M. A. Bierma-Zeinstra, Brian A. Hargreaves, Jos Runhaar, Frank W. J. Heijboer, Garry E. Gold, and Edwin H. G. Oei · 2019
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Sigpy: a python package for high performance iterative reconstruction
Frank Ong and Michael Lustig · 2019
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Prospective deployment of deep learning in MRI: A framework for important considerations, challenges, and recommendations for best practices
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Cited alongside, same era.
Unrolled optimization with deep priors
Steven Diamond, Vincent Sitzmann, Felix Heide, and Gordon Wetzstein · 2017
Cited alongside, same era.
Learning a variational network for reconstruction of accelerated MRI data
Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, and Florian Knoll · 2017
Cited alongside, same era.
Simultaneous bilateral-knee MR imaging
Feliks Kogan, Evan Levine, Akshay S. Chaudhari, Uchechukwuka D. Monu, Kevin Epperson, Edwin H.G. Oei, Garry E. Gold, and Brian A. Hargreaves · 2017
Cited alongside, same era.
Cluster analysis of quantitative mri t2 and t1
Uchechukwuka D Monu, Caroline D Jordan, Bonnie L Samuelson, Brian A Hargreaves, Garry E Gold, and Emily J McWalter · 2017
Cited alongside, same era.
A simple analytic method for estimating t2 in the knee from DESS
B. Sveinsson, A.S. Chaudhari, G.E. Gold, and B.A. Hargreaves · 2017
Cited alongside, same era.
Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet
Nicholas Bien, Pranav Rajpurkar, Robyn L. Ball, Jeremy Irvin, Allison Park, Erik Jones, Michael Bereket, Bhavik N. Patel, Kristen W. Yeom, Katie Shpanskaya, Safwan Halabi, Evan Zucker, Gary Fanton, Derek F. Amanatullah, Christopher F. Beaulieu, Geoffrey M. Riley, Russell J. Stewart, Francis G. Blankenberg, David B. Larson, Ricky H. Jones, Curtis P. Langlotz, Andrew Y. Ng, and Matthew P. Lungren · 2018
Cited alongside, same era.
Combined 5-minute double-echo in steady-state with separated echoes and 2-minute proton-density-weighted 2d FSE sequence for comprehensive whole-joint knee MRI assessment
Akshay S. Chaudhari, Kathryn J. Stevens, Bragi Sveinsson, Jeff P. Wood, Christopher F. Beaulieu, Edwin H.G. Oei, Jarrett K. Rosenberg, Feliks Kogan, Marcus T. Alley, Garry E. Gold, and Brian A. Hargreaves · 2018
Cited alongside, same era.
Akshay S. Chaudhari, Christopher M. Sandino, Elizabeth K. Cole, David B. Larson, Garry E. Gold, Shreyas S. Vasanawala, Matthew P. Lungren, Brian A. Hargreaves, and Curtis P. Langlotz · 2020
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Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge
Florian Knoll, Tullie Murrell, Anuroop Sriram, Nafissa Yakubova, Jure Zbontar, Michael Rabbat, Aaron Defazio, Matthew J. Muckley, Daniel K. Sodickson, C. Lawrence Zitnick, and Michael P. Recht · 2020
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fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning
Florian Knoll, Jure Zbontar, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzalv, Adriana Romero, Michael Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, and Yvonne W. Lui · 2020
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MONAI: Medical Open Network for AI, 3 2020
MONAI Consortium · 2020
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Compressed sensing: From research to clinical practice with deep neural networks: Shortening scan times for magnetic resonance imaging
Christopher M Sandino, Joseph Y Cheng, Feiyu Chen, Morteza Mardani, John M Pauly, and Shreyas S Vasanawala · 2020
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End-to-end variational networks for accelerated mri reconstruction
Anuroop Sriram, Jure Zbontar, Tullie Murrell, Aaron Defazio, C Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, and Patricia Johnson · 2020
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Diagnostic accuracy of quantitative multicontrast 5-minute knee MRI using prospective artificial intelligence image quality enhancement
Akshay S. Chaudhari, Murray J. Grissom, Zhongnan Fang, Bragi Sveinsson, Jin Hyung Lee, Garry E. Gold, Brian A. Hargreaves, and Kathryn J. Stevens · 2021
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Characterizing the transient response of knee cartilage to running: Decreases in cartilage t2 of female recreational runners
Hollis A Crowder, Valentina Mazzoli, Marianne S Black, Lauren E Watkins, Feliks Kogan, Brian A Hargreaves, Marc E Levenston, and Garry E Gold · 2021
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Measuring robustness in deep learning based compressive sensing
Mohammad Zalbagi Darestani, Akshay S Chaudhari, and Reinhard Heckel · 2021
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The international workshop on osteoarthritis imaging knee mri segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset
Arjun D Desai, Francesco Caliva, Claudia Iriondo, Aliasghar Mortazi, Sachin Jambawalikar, Ulas Bagci, Mathias Perslev, Christian Igel, Erik B Dam, Sibaji Gaj, et al · 2021
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Results of the 2020 fastMRI challenge for machine learning MR image reconstruction
Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, and Florian Knoll · 2021
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fastmri+: Clinical pathology annotations for knee and brain fully sampled multi-coil mri data
Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W Lui, Michael S Hansen, and Matthew P Lungren · 2021
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