From 13560d2f198cc72f06e01675e9ecee509ce5639a Mon Sep 17 00:00:00 2001 From: Matthew Muckley Date: Wed, 10 Nov 2021 09:31:23 -0500 Subject: [PATCH] Update dataset documentation links (#193) * Update dataset documentation links * First author star * Stats to props --- README.md | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index d9692943..319357b7 100644 --- a/README.md +++ b/README.md @@ -28,9 +28,18 @@ publications of the fastMRI project. ## Documentation -Documentation for the fastMRI dataset and baseline reconstruction performance -can be found in [our paper on arXiv](https://arxiv.org/abs/1811.08839). The -paper is updated on an ongoing basis for dataset additions and new baselines. +### The fastMRI Dataset + +There are multiple publications describing different subcomponents of the data +(e.g., brain vs. knee) and associated baselines. + +* **Project Summary, Datasets, Baselines:** [fastMRI: An Open Dataset and Benchmarks for Accelerated MRI ({J. Zbontar*, F. Knoll*, A. Sriram*} et al., 2018)](https://arxiv.org/abs/1811.08839) + +* **Knee Data:** [fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning ({F. Knoll*, J. Zbontar*} et al., 2020)](https://doi.org/10.1148/ryai.2020190007) + +* **Brain Dataset Properties:** [Supplemental Material](https://ieeexplore.ieee.org/ielx7/42/9526230/9420272/supp1-3075856.pdf?arnumber=9420272) of [Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction ({M. Muckley*, B. Riemenschneider*} et al., 2021)](https://doi.org/10.1109/TMI.2021.3075856) + +### Code Repository For code documentation, most functions and classes have accompanying docstrings that you can access via the `help` function in IPython. For example: @@ -85,9 +94,7 @@ and logging. ## Examples and Reproducibility The `fastmri_examples` and `banding_removal` folders include code for -reproducibility. The baseline models were used in the arXiv paper: - -[fastMRI: An Open Dataset and Benchmarks for Accelerated MRI ({J. Zbontar*, F. Knoll*, A. Sriram*} et al., 2018)](https://arxiv.org/abs/1811.08839) +reproducibility. The baseline models were used in the [arXiv paper](https://arxiv.org/abs/1811.08839). A brief summary of implementions based on papers with links to code follows. For completeness we also mention work on active acquisition, which is hosted