We present a new spatio-temporal denoising method for arterial spin labeling (ASL) 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.     «

We present a new spatio-temporal denoising method for arterial spin labeling (ASL) 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 me...     »