Abstract is missing.
- Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance ImagingAkshay Chaudhari, Zhongnan Fang, Jin Hyung Lee, Garry Gold, Brian A. Hargreaves. 3-11 [doi]
- ETER-net: End to End MR Image Reconstruction Using Recurrent Neural NetworkChangheun Oh, Dongchan Kim, Jun-Young Chung, Yeji Han, HyunWook Park. 12-20 [doi]
- Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based ReconstructionIlkay Öksüz, James R. Clough, Aurélien Bustin, Gastao Cruz, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King. 21-29 [doi]
- Complex Fully Convolutional Neural Networks for MR Image ReconstructionMuneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada, Phillip Ehses, Tony Stöcker, Martin Reuter 0001. 30-38 [doi]
- Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural NetworksFabian Balsiger, Amaresha Shridhar Konar, Shivaprasad Chikop, Vimal Chandran, Olivier Scheidegger, Sairam Geethanath, Mauricio Reyes 0001. 39-46 [doi]
- Improved Time-Resolved MRA Using k-Space Deep LearningEunju Cha, Eung-Yeop Kim, Jong Chul Ye. 47-54 [doi]
- Joint Motion Estimation and Segmentation from Undersampled Cardiac MR ImageChen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert. 55-63 [doi]
- Bayesian Deep Learning for Accelerated MR Image ReconstructionJo Schlemper, Daniel C. Castro, Wenjia Bai, Chen Qin, Ozan Oktay, Jinming Duan, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert. 64-71 [doi]
- Sparse-View CT Reconstruction Using Wasserstein GANsFranz Thaler, Kerstin Hammernik, Christian Payer, Martin Urschler, Darko Stern. 75-82 [doi]
- Detecting Anatomical Landmarks for Motion Estimation in Weight-Bearing Imaging of KneesBastian Bier, Katharina Aschoff, Christopher Syben, Mathias Unberath, Marc Levenston, Garry Gold, Rebecca Fahrig, Andreas K. Maier. 83-90 [doi]
- A U-Nets Cascade for Sparse View Computed TomographyAndreas Kofler, Markus Haltmeier, Christoph Kolbitsch, Marc Kachelrieß, Marc Dewey. 91-99 [doi]
- Approximate k-Space Models and Deep Learning for Fast Photoacoustic ReconstructionAndreas Hauptmann, Ben T. Cox, Felix Lucka, Nam Huynh, Marta M. Betcke, Paul C. Beard, Simon R. Arridge. 103-111 [doi]
- Deep Learning Based Image Reconstruction for Diffuse Optical TomographyHanene Ben Yedder, Aïcha BenTaieb, Majid Shokoufi, Amir Zahiremami, Farid Golnaraghi, Ghassan Hamarneh. 112-119 [doi]
- Image Reconstruction via Variational Network for Real-Time Hand-Held Sound-Speed ImagingValeriy Vishnevskiy, Sergio J. Sanabria, Orcun Goksel. 120-128 [doi]
- Towards Arbitrary Noise Augmentation - Deep Learning for Sampling from Arbitrary Probability DistributionsFelix Horger, Tobias Würfl, Vincent Christlein, Andreas K. Maier. 129-137 [doi]
- Left Atria Reconstruction from a Series of Sparse Catheter Paths Using Neural NetworksAlon Baram, Moshe Safran, Avi Ben-Cohen, Hayit Greenspan. 138-146 [doi]
- High Quality Ultrasonic Multi-line Transmission Through Deep LearningSanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alexander M. Bronstein, Michael Zibulevsky, Oleg V. Michailovich, Dan Adam, Diana Gaitini. 147-155 [doi]