Corpus ID: 53759905

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

@article{Zbontar2018fastMRIAO,
  title={fastMRI: An Open Dataset and Benchmarks for Accelerated MRI},
  author={J. Zbontar and F. Knoll and Anuroop Sriram and Matthew Muckley and Mary Bruno and Aaron Defazio and Marc Parente and Krzysztof J Geras and Joe Katsnelson and H. Chandarana and Zizhao Zhang and M. Drozdzal and A. Romero and M. Rabbat and P. Vincent and James Pinkerton and D. Wang and N. Yakubova and E. Owens and C. L. Zitnick and M. Recht and D. Sodickson and Y. Lui},
  journal={ArXiv},
  year={2018},
  volume={abs/1811.08839}
}

J. Zbontar, F. Knoll, +20 authors Y. Lui

Published 2018

Computer Science, Engineering, Physics, Mathematics

ArXiv

Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measurements has the potential to reduce medical costs, minimize stress to patients and make MRI possible in applications where it is currently prohibitively slow or expensive. We introduce the fastMRI dataset, a large-scale collection of both raw MR measurements and clinical MR images, that can be used for training and evaluation of machine-learning approaches to MR image reconstruction. By introducing standardized evaluation… CONTINUE READING

View PDF on arXiv

Save to Library

Create Alert

Cite

Launch Research Feed