Andrew Reader
Andrew Reader is a Professor of Imaging Sciences at King’s College London, United Kingdom. He received his Ph.D. in medical physics from the University of London in 1999 on the subject of PET image reconstruction.
Prior to joining the School of Biomedical Engineering and Imaging Sciences at King’s College London in 2014, he was a Canada Research Chair at McGill University and the Montreal Neurological institute for 6 years. He is an Associate Editor of IEEE TRPMS and has co-authored over 200 scientific outputs.
His main research interests include PET-MR, multi-modal image reconstruction and medical image analysis, all now with a primary emphasis on exploiting deep learning.
Abstract Prof. Reader Lectures:
This lecture starts from the fundamentals of tomographic medical image reconstruction (direct and iterative reconstruction methods) and then develops these into the broad spectrum of deep-learning approaches related to image reconstruction. These include direct inversion methods through to regularisation (analysis) and synthesis approaches using deep learning. Positron emission tomography (PET) will be the primary example, but the principles are applicable to other medical imaging modalities. The lecture also covers basic practical implementation principles using PyTorch to create trainable computational graphs for image reconstruction from sinograms.
The second part of the day the students will execute practical examples on their own laptops.
