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PET-MR Dataset

Simultaneously acquired positron emission tomography and magnetic resonance data of the brain, plus joint image reconstruction code.

We are making available an in vivo PET-MR dataset used in joint reconstruction experiments in our related publication (see Figure 8 in the paper cited below).

The data were acquired on a Siemens Biograph mMr during a 10-minute brain FDG-PET scan combined with an undersampled MPRAGE MR scan.

The dataset includes MR-receive coil sensitivity maps, PET attenuation correction maps, and scatter estimates.

Related Publication

Knoll F, Holler M, Koesters T, Otazo R, Bredies K, Sodickson DK.
Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer.
IEEE Trans Med Imaging. 2017 Jan;36(1):1-16. doi: 10.1109/TMI.2016.2564989

Please cite this work if you are using the PET-MR dataset in your research.

Get the Data

The software available on this page is provided free of charge and comes without any warranty. CAI²R and NYU Grossman School of Medicine do not take any liability for problems or damage of any kind resulting from the use of the files provided. Operation of the software is solely at the user’s own risk. The software developments provided are not medical products and must not be used for making diagnostic decisions.

The software is provided for non-commercial, academic use only. Usage or distribution of the software for commercial purpose is prohibited. All rights belong to the author (Florian Knoll) and NYU Grossman School of Medicine. If you use the software for academic work, please give credit to the author in publications and cite the related publications.

Please spell out your affiliation (e.g. "New York University" rather than "NYU").

Get the Code

Together with colleagues at Graz University, we are also sharing code for reproducing the reconstruction used in our related publication. The associated readme includes a detailed description of what the PET-MR data contain and how to use them.

Contact

Questions about this resource may be directed to Florian Knoll, PhD.