Meeting Banner
Abstract #2826

DCE-MRI Perfusion Analysis with L1-Norm Spatial Regularization

Michal Bartoš1, Michal Šorel1, Marie Mangová2, Pavel Rajmic2, Michal Standara3, and Radovan Jiřík4

1The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic, 2Department of Telecommunications, Brno University of Technology, Brno, Czech Republic, 3Masaryk Memorial Cancer Institute, Brno, Czech Republic, 4The Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic

DCE-MRI perfusion analysis suffers from low reliability, especially when 2nd-generation pharmacokinetic models are used to estimate perfusion parameter maps (voxel-by-voxel estimation) in low SNR conditions. These models provide estimates of plasma flow and capillary permeability in addition to the commonly used parameters Ktrans, kep. This contribution presents a method for estimation of perfusion maps using the tissue homogeneity model with incorporated spatial regularization in the form of total variation. The algorithm is based on the proximal minimization methods well established in image reconstruction problems. The use of state-of-the-art minimization and image regularization techniques stabilizes the estimates of perfusion parameter maps and keeps the computational demands low.

This abstract and the presentation materials are available to members only; a login is required.

Join Here