Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: fastMRI: An Open Dataset and Benchmarks for Accelerated MRI   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 criteria and a freely-accessible dataset,
our goal is to help the community make rapid advances in the state of the art
for MR image reconstruction. We also provide a self-contained introduction to
MRI for machine learning researchers with no medical imaging background.

21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
25
The categories of this paper are: patt-sol