7 citations · 7 across the 1 of their papers we have counts for
3 papers
Data-driven regularization parameter selection in dynamic MRI
Matti Hanhela, Olli Gröhn, Mikko Kettunen +3
In dynamic MRI, sufficient time resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the…
Temporal Huber regularization for DCE-MRI
Matti Hanhela, Mikko Kettunen, Olli Gröhn +2
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to study microvascular structure and tissue perfusion. In DCE-MRI a bolus of gadolinium based contrast agent…
Dynamic MRI Reconstruction from Undersampled Data with an Anatomical Prescan
Julian Rasch, Ville Kolehmainen, Riikka Nivajärvi +4
The goal of dynamic magnetic resonance imaging (dynamic MRI) is to visualize tissue properties and their local changes over time that are traceable in the MR signal. We propose a n…