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Deep Transcranial Adaptive Ultrasound Localization Microscopy of the Human Brain Vascularization: supplemental software and data

Charlie Demené; Justine Robin; Alexandre Dizeux; Baptiste Heiles; Mathieu Pernot; Mickael Tanter; Fabienne Perren

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.
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