• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 18 matches

• 2018
• 
  Fabian Balsiger, Amaresha Shridhar Konar, Shivaprasad Chikop, Vimal Chandran, Olivier Scheidegger, Sairam Geethanath, Mauricio Reyes:
  Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks. MLMIR@MICCAI 2018: 39-46
• 
  Alon Baram, Moshe Safran, Avi Ben-Cohen, Hayit Greenspan:
  Left Atria Reconstruction from a Series of Sparse Catheter Paths Using Neural Networks. MLMIR@MICCAI 2018: 138-146
• 
  Bastian Bier, Katharina Aschoff, Christopher Syben, Mathias Unberath, Marc E. Levenston, Garry Gold, Rebecca Fahrig, Andreas K. Maier:
  Detecting Anatomical Landmarks for Motion Estimation in Weight-Bearing Imaging of Knees. MLMIR@MICCAI 2018: 83-90
• 
  Eunju Cha, Eung-Yeop Kim, Jong Chul Ye:
  Improved Time-Resolved MRA Using k-Space Deep Learning. MLMIR@MICCAI 2018: 47-54
• 
  Akshay Chaudhari, Zhongnan Fang, Jin Hyung Lee, Garry Gold, Brian A. Hargreaves:
  Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging. MLMIR@MICCAI 2018: 3-11
• 
  Muneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada, Phillip Ehses, Tony Stöcker, Martin Reuter:
  Complex Fully Convolutional Neural Networks for MR Image Reconstruction. MLMIR@MICCAI 2018: 30-38
• 
  Andreas Hauptmann, Ben T. Cox, Felix Lucka, Nam Huynh, Marta M. Betcke, Paul C. Beard, Simon R. Arridge:
  Approximate k-Space Models and Deep Learning for Fast Photoacoustic Reconstruction. MLMIR@MICCAI 2018: 103-111
• 
  Felix Horger, Tobias Würfl, Vincent Christlein, Andreas K. Maier:
  Towards Arbitrary Noise Augmentation - Deep Learning for Sampling from Arbitrary Probability Distributions. MLMIR@MICCAI 2018: 129-137
• 
  Andreas Kofler, Markus Haltmeier, Christoph Kolbitsch, Marc Kachelrieß, Marc Dewey:
  A U-Nets Cascade for Sparse View Computed Tomography. MLMIR@MICCAI 2018: 91-99
• 
  Changheun Oh, Dongchan Kim, Jun-Young Chung, Yeji Han, HyunWook Park:
  ETER-net: End to End MR Image Reconstruction Using Recurrent Neural Network. MLMIR@MICCAI 2018: 12-20
• 
  Ilkay Öksüz, James R. Clough, Aurélien Bustin, Gastão Cruz, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
  Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction. MLMIR@MICCAI 2018: 21-29
• 
  Chen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert:
  Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image. MLMIR@MICCAI 2018: 55-63
• 
  Jo Schlemper, Daniel Coelho de Castro, Wenjia Bai, Chen Qin, Ozan Oktay, Jinming Duan, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
  Bayesian Deep Learning for Accelerated MR Image Reconstruction. MLMIR@MICCAI 2018: 64-71
• 
  Franz Thaler, Kerstin Hammernik, Christian Payer, Martin Urschler, Darko Stern:
  Sparse-View CT Reconstruction Using Wasserstein GANs. MLMIR@MICCAI 2018: 75-82
• 
  Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alexander M. Bronstein, Michael Zibulevsky, Oleg V. Michailovich, Dan Adam, Diana Gaitini:
  High Quality Ultrasonic Multi-line Transmission Through Deep Learning. MLMIR@MICCAI 2018: 147-155
• 
  Valeriy Vishnevskiy, Sergio J. Sanabria, Orcun Goksel:
  Image Reconstruction via Variational Network for Real-Time Hand-Held Sound-Speed Imaging. MLMIR@MICCAI 2018: 120-128
• 
  Hanene Ben Yedder, Aïcha BenTaieb, Majid Shokoufi, Amir Zahiremami, Farid Golnaraghi, Ghassan Hamarneh:
  Deep Learning Based Image Reconstruction for Diffuse Optical Tomography. MLMIR@MICCAI 2018: 112-119
• 
  Florian Knoll, Andreas K. Maier, Daniel Rueckert:
  Machine Learning for Medical Image Reconstruction - First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11074, Springer 2018, ISBN 978-3-030-00128-5 [contents]