Sensitivity of a partially learned model‐based reconstruction algorithm

Abstract

We replace part of a model‐based iterative algorithm with a convolutional neural network in order to improve the quality of tomography reconstructions. We analyse its robustness against uncertainties in the image and uncertainties in system settings. Results are presented for the application of photoacoustic tomography in a limited angle setup.