Mathematical Methods for Spatiotemporal ImagingMS73

Spatiotemporal imaging arises in many applications and the minisymposium aims to bring together leading experts and young researchers in the processing of such imaging data. The field is undergoing rapid development where a variety of mathematical methods (shape theory, regularization method, local analysis, algorithm) play a pivotal role in improving the reconstruction and analysis of spatiotemporal images, e.g. motion estimation in reconstruction (4D CBCT, pulmonary PET-CT, cardiac SPECT-CT, electron microscopy), predicting the evolution of a disease. The high diversity in mathematical techniques makes it very challenging for a single researcher to embrace the full spectrum of this rapidly evolving field.

Large diffeomorphic deformation based image reconstruction method for spatiotemporal imaging
Chong Chen (LSEC, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences)
Optical flow constrained joint motion estimation and reconstruction for dynamic inverse problems
Andreas Hauptmann (University College London)
4D Reconstruction of motion corrected dynamic MR PET list mode data with regularization in the time domain
Fjedor Gaede (Institute for Computational and Applied Mathematics, University of Münster)
Generalized Sinkhorn Iterations for Regularizing Inverse Problems Using Optimal Mass Transport
Axel Ringh (KTH - Royal Institute of Technology)
Joint Motion Estimation and Source Identification with an Application to the Analysis of Cell Membranes
Lukas F. Lang (University of Cambridge)
Respiratory motion correction in PET/CT and PET/MR
Elise Emond (University College London)
Learning digital models of Alzheimer’s Disease progression
Igor Koval (Brain and Spine Institute, INRIA)
Chong Chen (LSEC, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences)
Barbara Gris (Laboratoire Jacques-Louis Lions)
Ozan Öktem (KTH - Royal Institute of Technology)
bayesian methods, computational methods, computed tomography, computer vision, image reconstruction, image registration, integral equations for image analysis, inverse problems, local analysis, nonlinear optimization, regularization method, shape theory, spatiotemporal imaging, statistical inverse estimation methods