Samples of MR Images
Pollard, T., Moody, B. E., Lehman, L., Gow, B., Fernandes, C., Xie, C., Johnson, A., Mark, R. G., & Heldt, T. (2026). PhysioNet as a global platform for biomedical research. Nature Health. https://doi.org/10.1038/s44360-026-00096-z. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC13641116/
Data Description
These magnetic resonance angiography (MRA) images show coronal slices acquired from consecutive anteroposterior positions within the torso. The study was performed on a 1.5T General Electric (GE) Signa imaging system with gadolinium-contrast-enhancement for visualization of the cardiopulmonary vasculature. The pulse sequence used was a 3D time-of-flight fast spoiled gradient recalled acquisition in steady state (FSPGR, TR=6.3, TE=1.4, NEX=1, FOV = 40cm, slice thickness = 1.2mm).
This sample image contains 76 frames. It is available in DICOM format (E1154S7I.dcm), as an animated GIF (E1154S7I.gif), as .ogg, .mp4, .webm, and .swf animations (one of which is shown above), or as individual PNG-format frames (see below).
The original DICOM image was converted into GIF and PNG formats using reformat-dicom, a script that makes use of the ImageMagick convert utility (included in most Linux distributions and available freely for most other platforms from http://www.imagemagick.org).
Contributors
We wish to thank Dr. Godtfred Holmvang for making these data available here.
Cited by
1 publication cites this project. The most recent are listed below.
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A parallel hierarchical tensor product method for n-dimensional interpolation in the Fourier domain
Hsin-Chia Chen, Hao Chiao Yang, Yu-Chieh Chao et al. International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), 2021.
Citation data from OpenAlex. Papers that use the project without citing it may be missing.
Files
Total uncompressed size: 70.8 MB.
Access the files
- Download the ZIP file (70.8 MB)
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Download with the PhysioNet Python package:
physionet download images --version 1.0.0
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Download the files using your terminal:
wget -r -N -c -np https://physionet.org/files/images/1.0.0/
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Download the files using AWS command line tools:
aws s3 sync --no-sign-request s3://physionet-open/images/1.0.0/ DESTINATION