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ORCIDMLMIR@MICCAI 2021: Strasbourg, France
- Nandinee Fariah Haq
, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo:
Machine Learning for Medical Image Reconstruction - 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 12964, Springer 2021, ISBN 978-3-030-88551-9
Deep Learning for Magnetic Resonance Imaging
- Alan Q. Wang, Adrian V. Dalca, Mert R. Sabuncu:
HyperRecon: Regularization-Agnostic CS-MRI Reconstruction with Hypernetworks. 3-13 - Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik:
Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation. 14-24 - Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. 25-34 - Mert Acar, Tolga Çukur, Ilkay Öksüz:
Self-supervised Dynamic MRI Reconstruction. 35-44 - Zhengnan Huang, Jonghyun Bae, Patricia M. Johnson, Terlika Sood, Laura Heacock, Justin Fogarty, Linda Moy, Sungheon Gene Kim, Florian Knoll:
A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction. 45-53 - Yilmaz Korkmaz, Mahmut Yurt, Salman Ul Hassan Dar, Muzaffer Özbey, Tolga Çukur:
Deep MRI Reconstruction with Generative Vision Transformers. 54-64 - Ahana Roy Choudhury, Sachin R. Jambawalikar, Piyush Kumar, Venkat Sumanth Reddy Bommireddy:
Distortion Removal and Deblurring of Single-Shot DWI MRI Scans. 65-75 - Zhiwen Wang, Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang:
One Network to Solve Them All: A Sequential Multi-task Joint Learning Network Framework for MR Imaging Pipeline. 76-85 - Elena Martín-González, Ebraham Alskaf, Amedeo Chiribiri, Pablo Casaseca-de-la-Higuera, Carlos Alberola-López, Rita Gouveia Nunes, Teresa Correia:
Physics-Informed Self-supervised Deep Learning Reconstruction for Accelerated First-Pass Perfusion Cardiac MRI. 86-95
Deep Learning for General Image Reconstruction
- Mikhail Papkov, Kenny Roberts, Lee Ann Madissoon, Jarrod Shilts, Ömer Bayraktar, Dmytro Fishman, Kaupo Palo, Leopold Parts:
Noise2Stack: Improving Image Restoration by Learning from Volumetric Data. 99-108 - Dave Van Veen, Ben A. Duffy, Long Wang, Keshav Datta, Tao Zhang, Greg Zaharchuk, Enhao Gong:
Real-Time Video Denoising to Reduce Ionizing Radiation Exposure in Fluoroscopic Imaging. 109-119 - Qing Ma, Jae Chul Koh, Won-Sook Lee:
A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution. 120-129 - Canyu Yang, Dennis Eschweiler, Johannes Stegmaier:
Semi- and Self-supervised Multi-view Fusion of 3D Microscopy Images Using Generative Adversarial Networks. 130-139
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