Published September 12, 2022
| Version v1
Dataset
Open
Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI
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.
Files
Files
(36.9 GB)
| Name | Size | Download all |
|---|---|---|
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md5:8af9f05ffbdea19340acaa562757ebef
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13.1 GB | Download |
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md5:803f99666557fad7d275186dec62ec3c
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23.8 GB | Download |