Speaker
Dr
Bastien Milani
Description
This abstract aims to describe MRI reconstructions in the general framework of finite-dimensional inner-product spaces. We explain that image-space preconditioning (ISP) and data-space preconditioning (DSP) can be formulated as non-conventional inner-products. This allows to introduce image-space preconditioning in the variational formulation of the MRI reconstruction problem (in an algorithm-independent way) and to propagate it in principle in all iterative reconstructions, including many iterative deep-learning and compressed-sensing reconstructions where preconditioning is lacking until now.