Preconditioning linear systems from deformable 3D medical image registration using tensor train format

Justin Buhendwa Nyenyezi (Orateur)

Activité: Types de discours ou de présentationPrésentation orale

Description

In medical image analysis, deformable 3D image registration takes a relatively long time, especially for non-parametric transformations, for which the computing time may be quite troublesome and not even feasible for some clinical applications. Modelled as a variational problem, this registration problem needs to solve a sequence of linear systems during the optimization process. Much of the time is spent in the solution of these linear systems. Indeed, although these systems are sparse and structured, they are very large and ill conditioned. In this talk, we present and study a preconditioning technique to accelerate the solution of these linear systems using tensor train format. Appropriate preconditioners in tensor train format offer a good compromise between complexity and precision.
Période2 févr. 20173 févr. 2017
Conservé àORBEL: Belgian Operational Research (OR) Society, 31st conference, Belgique
Niveau de reconnaissanceNational