Fri, Mar 06, 2020 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Rudolf Stollberger, Graz University of Technology, Institute of Medical Engineering
Talk Title: Variational Reconstruction of Highly Undersampled 3D Multiple Frame Acquisitions
Series: Medical Imaging Seminar Series
Abstract: Time dependent or quantitative multiple frame acquisitions are particular well suited for the combination of accelerated acquisition and sophisticated iterative reconstruction techniques with spatial-temporal regularization or model based approaches. In this presentation the potential of variational reconstruction for dynamic MRI, for ASL and for model based quantification is explored. Although the applications are quite different, some basic principles are common to all.
For dynamic data iterative reconstruction with infimal convolution of total generalized variation (ICTGV) functionals has shown to allow temporal resolution below 1s for 3D measurements with 40 slices (3202) with excellent suppression of sub-sampling artifacts. This approach will be compared with a variational network for dynamic multi-coil cardiac data. Another example exists for accelerated time encoded CAIPIRINHA ASL data. For this application, the whole brain can be acquired within a single shot which increases the robustness against motion compared to standard segmented acquisition. A third application area consists in quantitative MRI. Model based reconstruction allow the determination of 3D isotropic T1 maps (1mm3) with an acquisition time of 1.8-“1.1 s/slice for the variable flip angle method (VFA). The variational techniques can process 4D array coil data, which is still a challenge for DL-based approaches. Reconstruction times start at about 4 minutes for 4D-ASL data and are somewhat longer for dynamic MRI, but can be many times longer for model-based reconstruction of 4D qMRI data with a nonlinear signal model like VFA.
Host: Krishna Nayak, firstname.lastname@example.org
Audiences: Everyone Is Invited
Contact: Talyia White