In photoacoustic imaging, as in many high resolution modalities, the major bottle neck is the acquisition time of finely spatially sampled data. In particular for imaging of dynamical processes, this results in incomplete data. In this talk we are going to discuss different aspects of variational methods for photoacoustic imaging using spatio-temporal regularization via optical flow constraint which allow us maintaining good quality of the reconstruction from severely subsampled/compressed dynamic data.

This presentation is part of Minisymposium “MS6 - Time-dependent problems in imaging (2 parts)”
organized by: Thomas Schuster (Saarland University) , Anne Wald (Saarland University) .

Authors:

Marta Betcke (University College London)

Simon Arridge (University College London)

Beard Paul (UCL)

Ben Cox (Department of Medical Physics, University College London)

Nam Huynh ()

Felix Lucka (CWI & UCL)

Bolin Pan (University College London)

Edward Zhang (UCL)

Keywords:

computed tomography, image reconstruction, inverse problems