Published September 12, 2022
| Version v1
Dataset
Open
Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI
Authors/Creators
- 1. Siemens Healthineers International AG
- 2. Lausanne University Hospital
- 3. University of Lausanne
- 4. Ecole Polytechnique Federale de Lausanne
Description
This repository contains datasets acquired for the MELBA paper (https://www.melba-journal.org/papers/2022:022.html) Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI. In particular, this repository contains fully sampled raw measurement data (k-space) from high resolution MRI scans of a phantom and a collection of fruits and vegetables. The prospectively accelerated data acquired for our paper can be found at http://mridata.org. The data is stored in ISMRMRD format in a .h5 file.