Meeting Banner
Abstract #3634

A Spatio-temporal Denoising Approach based on Total Variation Regularization for Arterial Spin Labeling

Cagdas Ulas1,2, Stephan Kaczmarz3, Christine Preibisch3, Jonathan I. Sperl2, Marion I. Menzel2, Axel Haase4, and Bjoern H. Menze1

1Department of Computer Science, Technische Universität München, Munich, Germany, 2GE Global Research, Munich, Germany, 3Department of Neuroradiology, Technische Universität München, Munich, Germany, 4Zentralinstitut für Medizintechnik, Technische Universität München, Munich, Germany

We present a new spatio-temporal denoising method for arterial spin labelling MR image repetitions, and mainly aim to improve the quality of perfusion-weighted images and cerebral blood flow (CBF) maps obtained from a subset of all dynamics available. Our technique is based on a two-step 3D total variation regularization, which is applied to subsets of control/label pairs in the first step and to resulting perfusion-weighted (difference) images in the second step. We demonstrate that our method leads to improved quality of perfusion-weighted images and CBF maps compared to existing spatial filtering techniques in short computation time.

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

Join Here