We are sharing a collection of voluminous, expertly curated, and rigorously deidentified data sets for machine learning research on accelerating MRI.
The fastMRI dataset includes raw data from 1,500 fully sampled knee MRIs, DICOM images from 10,000 clinical knee MRIs, and raw data from nearly 7,000 fully sampled brain MRIs.
fastMRI is a collaborative partnership between CAI2R and Meta AI Research aimed at making routine clinical MRI exams up to 10 times faster.
fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning.
Radiol Artif Intell. 2020 Jan 29;2(1):e190007. doi: 10.1148/ryai.2020190007
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI.
arXiv:1811.08839 21 Nov 2018.
Please cite these works if you are using fastMRI data in your research (see section 6 of the data sharing agreement on the fastMRI Dataset download request page, linked below).
Visit fastmri.org to learn about machine learning MRI reconstruction challenges and recent project milestones.
Patricia Johnson, who researches machine learning image reconstruction, talks about faster MRI, visual preferences, and diagnostic interchangeability.
Florian Knoll, incoming chair of imaging at University of Erlangen–Nuremberg, talks about his background, not being greedy, and why he does what he does.