Beyond the Patterns 17 Emil Sidky Inverse problems in imaging and evidence for solution by CNNs

It would have been great to welcome Emil to the Bergkirchweih this year. Unfortunately, the festival was cancelled. Yet, we still have the pleasure to have Emil virtually here in Erlangen Abstract: This talk examines the claim made in the literature that illposed inverse problems associated with image reconstruction in computed tomography (CT) can be solved with a convolutional neural network (CNN). To lay the groundwork, a brief overview of inverse problems will be given including a discussion on what makes an inverse problem illposed and what constitutes its solution. Examples of how inverse problem investigations play a role in CT image reconstruction will be presented in order to appreciate the value of the generalizable knowledge gained in such studies. Having set the stage, the talk will the discuss the evidence that deeplearning with convolutional neural networks solve the CT inverse problem. Finally, I will cover our own investigation into the use of CNNs to solve the sparseview CT inverse probl