Iterative image reconstruction and deep learning
Blending deep learning and iterative image reconstruction has shown great promise to obtain high quality reconstructions from noisy, sub-sampled data and is therefore hot topic in inverse problems at the moment. We adopted an particular approach to enhance the reconstruction of blood vessel structures from sub-sampled, limited-view 3D photoacoustic tomography (PAT) in vivo. Many thanks to Andreas Hauptmann, who did the main work for this exciting project. The paper with all the results can be found on arXiv.