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3DPAT_DGD

This repository will collect codes accompanying the publication: Hauptmann et al., Model based learning for accelerated, limited-view 3D photoacoustic tomography, IEEE Transactions on Medical Imaging, 2018: https://doi.org/10.1109/TMI.2018.2820382

Scripts need Matlab, k-wave toolbox, Python, and tensorflow

Note: Codes are complete for DGD. Network phantom data for simulated test cases added.

  • 19 January 2018: First commit
  • 29 January 2018: k-wave wrapper added and evaluation of model
  • 20 March 2018: network data (DGD) and simulated phantoms added

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