Tomographic image reconstruction with learnt priors

Lecturer: Marta Betcke (UCL CMIC and CIP)

Recent advances in deep learning for tomographic reconstructions have shown a great promise to create accurate and high quality images from subsampled measurements in a time considerably shorter than needed by the established nonlinear regularisation methods such as e.g. Total Variation. This new paradigm also offers a new implicit way of expressing prior knowledge through training on a class of images with expected characteristics.