Transthoracic contrast echocardiography data of a patient for super-resolution ultrasound localisation microscopy
<p>We provide sample contrast echocardiography datasets used for generation of super-resolution ultrasound localisation microscopy (ULM) images as reported in the following paper:</p> <div> <div>Jipeng Yan, Biao Huang, Johanna Tonko, Matthieu Toulemonde, Joseph Hansen-Shearer, Qingyuan Tan, Kai Riemer, Konstantinos Ntagiantas, Rasheda A Chowdhury, Pier D Lambiase, Roxy Senior, Meng-Xing Tang. Transthoracic Ultrasound Localization Microscopy of Myocardial Vasculature in Patients, Nature Biomedical Engineering, 2024. DOI: (<a href="https://www.nature.com/articles/s41551-024-01206-6" target="_blank" rel="noopener noreferrer">10.1038/s41551-024-01206-6</a>).</div> <div> </div> <div>The sample datasets include:</div> <div> </div> <div>"LogCompressedCEUS.mp4' is a video of CEUS images gated within one cardiac cycle after motion correction and log compression (acquistion time: 0.36s).</div> <div> </div> <div>"LinearScaleCEUS.mat" is a Matlab data file containing CEUS images after motion correction.</div> <div> </div> <div>"LinearScaleCEUSAfterNoiseReduction.mat' is a Matlab data file containing above CEUS images with noise reduced, which can be processed with our SRUS software (<a href="https://github.com/JipengYan1995/SRUSSoftware">JipengYan1995/SRUSSoftware</a>) for localisation and tracking (A brief tutorial can be found in "Usage of sample data in SRUS Software.docx").</div> <div> </div> <div>"RcvDataSample.mat' is a Matlab data file containing RF data in channels;</div> <div> </div> <div>"BFInformation.mat' is a Matlab data file containing parameters for beamforming;</div> <div> </div> <div>"Data Description.txt" contains more detailed descriptions of above data.</div> <div> </div> </div> <p><strong>Data from all the 10 cardiac cycles of this patient will be available in the future.</strong></p> <p>If you have any questions, please contact Meng-Xing Tang (email: mengxing.tang@imperial.ac.uk).</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0
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