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NetData
phantomData
Call_model_3DVessels.m
EVAL_DGD_Load.py
EVAL_DGD_iteration.py
README.md
evalFull_DGD_mainScript.m
kWaveWrapper.m
setting.mat

README.md

3DPAT_DGD

This repository will collect codes accompanying the publication: Hauptmann et al., Model based learning for accelerated, limited-view 3D photoacoustic tomography, https://arxiv.org/abs/1708.09832

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