10.5281/zenodo.4048550
https://zenodo.org/records/4048550
oai:zenodo.org:4048550
Charlie Demené
Charlie Demené
0000-0002-5329-700X
Physics for Medicine Paris, Inserm, ESPCI Paris, PSL Research University, CNRS
Justine Robin
Justine Robin
Physics for Medicine Paris, Inserm, ESPCI Paris, PSL Research University, CNRS
Alexandre Dizeux
Alexandre Dizeux
Physics for Medicine Paris, Inserm, ESPCI Paris, PSL Research University, CNRS
Baptiste Heiles
Baptiste Heiles
Physics for Medicine Paris, Inserm, ESPCI Paris, PSL Research University, CNRS
Mathieu Pernot
Mathieu Pernot
Physics for Medicine Paris, Inserm, ESPCI Paris, PSL Research University, CNRS
Mickael Tanter
Mickael Tanter
Physics for Medicine Paris, Inserm, ESPCI Paris, PSL Research University, CNRS
Fabienne Perren
Fabienne Perren
Department of Clinical Neurosciences, HUG, LUNIC Laboratory Geneva Neurocenter, Faculty of Medicine, University of Geneva, Switzerland
Deep Transcranial Adaptive Ultrasound Localization Microscopy of the Human Brain Vascularization: supplemental software and data
Zenodo
2020
2020-11-03
eng
10.5281/zenodo.4048549
1.0
Creative Commons Attribution 4.0 International
We provide here sample data and basic sample codes (matlab) to illustrate the main concepts and techniques described in the manuscript entitled "Deep Transcranial Adaptive Ultrasound Localization Microscopy of the Human Brain Vascularization", to be published (at the date of the upload on the Zenodo repository) in the Nature Biomedical Engineering journal. It illustrates the most important steps of the processing routine, per se:
Beamforming (image formation): we supply raw RF data and the matlab based beamforming routine.
Aberration correction: we supply a demo code detailing the important steps of aberration correction. Output is an aberration correction profile that can be fed into the beamforming routine, and a image with aberration correction is produced.
Filtering: we supply the beamformed data (similar to the output of the 2 previous bullet points), SVD filtering routine and display code for visualization of the microbubbles.
We provide super-localisation data based on the previous data, along with display code for overlay with the raw data. We also provide code for visualisation of the bubble density image resulting from this process.