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Deep Learning (DL) has shown potential in accelerating Magnetic Resonance Image acquisition and reconstruction.
The association of bone marrow lesions with pain in knee osteoarthritis
David T Felson, Christine E Chaisson, Catherine L Hill, Saara MS Totterman, M Elon Gale, Katherine M Skinner, Lewis Kazis, and Daniel R Gale · 2001
Earlier work this paper cites.
Bone marrow edema and its relation to progression of knee osteoarthritis
David T Felson, Sara McLaughlin, Joyce Goggins, Michael P LaValley, M Elon Gale, Saara Totterman, Wei Li, Catherine Hill, and Daniel Gale · 2003
Earlier work this paper cites.
Osteoarthritis: Mr imaging findings in different stages of disease and correlation with clinical findings
Thomas M Link, Lynne S Steinbach, Srinka Ghosh, Michael Ries, Ying Lu, Nancy Lane, and Sharmila Majumdar · 2003
Earlier work this paper cites.
Whole-organ magnetic resonance imaging score (worms) of the knee in osteoarthritis
CG Peterfy, A Guermazi, S Zaim, PFJ Tirman, Y Miaux, D White, M Kothari, Y Lu, K Fye, S Zhao, et al · 2004
Earlier work this paper cites.
Parallel mr imaging: a user’s guide
James F Glockner, Houchun H Hu, David W Stanley, Lisa Angelos, and Kevin King · 2005
Earlier work this paper cites.
Sparse mri: The application of compressed sensing for rapid mr imaging
Michael Lustig, David Donoho, and John M Pauly · 2007
Earlier work this paper cites.
Evolution of semi-quantitative whole joint assessment of knee oa: Moaks (mri osteoarthritis knee score)
David J Hunter, Ali Guermazi, Grace H Lo, Andrew J Grainger, Philip G Conaghan, Robert M Boudreau, and Frank W Roemer · 2011
Earlier work this paper cites.
Random search for hyper-parameter optimization
James Bergstra and Yoshua Bengio · 2012
Earlier work this paper cites.
Oarsi guidelines for the non-surgical management of knee osteoarthritis
Timothy E McAlindon, R_R Bannuru, MC Sullivan, NK Arden, Francis Berenbaum, SM Bierma-Zeinstra, GA Hawker, Yves Henrotin, DJ Hunter, H Kawaguchi, et al · 2014
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Explaining and harnessing adversarial examples
Ian Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Can structural joint damage measured with mr imaging be used to predict knee replacement in the following year?
Frank W Roemer, C Kent Kwoh, Michael J Hannon, David J Hunter, Felix Eckstein, Zhijie Wang, Robert M Boudreau, Markus R John, Michael C Nevitt, and Ali Guermazi · 2015
Earlier work this paper cites.
Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 0.5 mb model size
Forrest N Iandola, Song Han, Matthew W Moskewicz, Khalid Ashraf, William J Dally, and Kurt Keutzer · 2016
Earlier work this paper cites.
Mri findings associated with development of incident knee pain over 48 months: data from the osteoarthritis initiative
Gabby B Joseph, Stephanie W Hou, Lorenzo Nardo, Ursula Heilmeier, Michael C Nevitt, Charles E McCulloch, and Thomas M Link · 2016
Earlier work this paper cites.
Exploring the landscape of spatial robustness
Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, and Aleksander Madry · 2017
Earlier work this paper cites.
Interpretable explanations of black boxes by meaningful perturbation
Ruth C Fong and Andrea Vedaldi · 2017
Earlier work this paper cites.
Adversarial examples for generative models
Jernej Kos, Ian Fischer, and Dawn Xiaodong Song · 2017
Earlier work this paper cites.
Adversarial examples in the physical world
Alexey Kurakin, Ian Goodfellow, and Samy Bengio · 2017
Earlier work this paper cites.
Synthesizing robust adversarial examples
Anish Athalye, Logan Engstrom, Andrew Ilyas, and Kevin Kwok · 2018
Cited alongside, same era.
Adversarial examples from computational constraints
Sébastien Bubeck, Eric Price, and Ilya Razenshteyn · 2018
Cited alongside, same era.
Distribution matching losses can hallucinate features in medical image translation
Joseph Paul Cohen, Margaux Luck, and Sina Honari · 2018
Cited alongside, same era.
Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S Schoenholz, Maithra Raghu, Martin Wattenberg, and Ian Goodfellow · 2018
Cited alongside, same era.
Physical attacks in dermoscopy: An evaluation of robustness for clinical deep-learning
David Kügler, Andreas Bucher, Johannes Kleemann, Alexander Distergoft, Ali Jabhe, Marc Uecker, Salome Kazeminia, Johannes Fauser, Daniel Alte, Angeelina Rajkarnikar, et al · 2018
Cited alongside, same era.
Robustifying deep networks for image segmentation
Zheng Liu, Jinnian Zhang, Varun Jog, Po-Ling Loh, and Alan B McMillan · 2019
Later among the works it cites.
The curse of concentration in robust learning: Evasion and poisoning attacks from concentration of measure
Saeed Mahloujifar, Dimitrios I Diochnos, and Mohammad Mahmoody · 2019
Later among the works it cites.
Invert to learn to invert
Patrick Putzky and Max Welling · 2019
Later among the works it cites.
i-rim applied to the fastmri challenge
Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan Caan, and Max Welling · 2019
Later among the works it cites.
Image synthesis with a single (robust) classifier
Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, and Aleksander Madry · 2019
Later among the works it cites.
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
Cited alongside, same era.
Differentiable abstract interpretation for provably robust neural networks
Matthew Mirman, Timon Gehr, and Martin Vechev · 2018
Cited alongside, same era.
Certified defenses against adversarial examples
Aditi Raghunathan, Jacob Steinhardt, and Percy Liang · 2018
Cited alongside, same era.
Adversarially robust generalization requires more data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, and Aleksander Madry · 2018
Cited alongside, same era.
Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong and Zico Kolter · 2018
Cited alongside, same era.
Spatially transformed adversarial examples
Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, and Dawn Song · 2018
Cited alongside, same era.
fastmri: An open dataset and benchmarks for accelerated mri
Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J Geras, Joe Katsnelson, Hersh Chandarana, et al · 2018
Cited alongside, same era.
Robustness may be at odds with accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, and Aleksander Madry · 2019
Later among the works it cites.
Interpretable explanations of black box classifiers applied on medical images by meaningful perturbations using variational autoencoders
Hristina Uzunova, Jan Ehrhardt, Timo Kepp, and Heinz Handels · 2019
Later among the works it cites.
On instabilities of deep learning in image reconstruction and the potential costs of ai
Vegard Antun, Francesco Renna, Clarice Poon, Ben Adcock, and Anders C Hansen · 2020
Closest in time.
Adversarial training and provable defenses: Bridging the gap
Mislav Balunovic and Martin Vechev · 2020
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Realistic adversarial data augmentation for mr image segmentation
Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, and Daniel Rueckert · 2020
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Addressing the false negative problem of deep learning mri reconstruction models by adversarial attacks and robust training
Kaiyang Cheng, Francesco Calivá, Rutwik Shah, Misung Han, Sharmila Majumdar, and Valentina Pedoia · 2020
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Machine learning for image reconstruction
Kerstin Hammernik and Florian Knoll · 2020
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Osteoarthritis year in review 2019: epidemiology and therapy
M Kloppenburg and F Berenbaum · 2020
Closest in time.
Matthew J Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, et al · 2020
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Using deep learning to accelerate knee mri at 3t: Results of an interchangeability study
Michael P Recht, Jure Zbontar, Daniel K Sodickson, Florian Knoll, Nafissa Yakubova, Anuroop Sriram, Tullie Murrell, Aaron Defazio, Michael Rabbat, Leon Rybak, et al · 2020
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Simulating single-coil mri from the responses of multiple coils
Mark Tygert and Jure Zbontar · 2020
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