Ingmar Middelhoff1, Matthias Schlögl2, Adrián Martín Fernández3, Silvio Fanzon4,5, Kristian Bredies4,5, and Rudolf Stollberger1,5
1Institute of Medical Engineering, TU Graz, Graz, Austria, 2Solgenium OG, Linz, Austria, 3Department of Information and Communications Technologies, Pompeu Fabra University, Barcelona, Spain, 4Institute of Mathematics and Scientific Computing, NAWI Graz, University of Graz, Graz, Austria, 5BioTechMed-Graz, Graz, Austria
1Institute of Medical Engineering, TU Graz, Graz, Austria, 2Solgenium OG, Linz, Austria, 3Department of Information and Communications Technologies, Pompeu Fabra University, Barcelona, Spain, 4Institute of Mathematics and Scientific Computing, NAWI Graz, University of Graz, Graz, Austria, 5BioTechMed-Graz, Graz, Austria
An Optimal Transport based reconstruction for motion-afflicted data is tested which yields an image series and pixel-wise motion fields. Reconstructions based on simulated single-coil 4-fold undersampled k-space time-series data show good image quality.
A visualization of the reconstruction concept: A moving object is measured in a series of undersampled k-spaces. In this abstract, we simulated a 4-times acceleration per k-space with the 8 center k-space lines being measured additionally. The OT reconstruction allows not only to recover the image-series, but also the momentum fields of the object. For illustration purposes, only every second frame is shown.
Zoom-in on the results from figure 2: The reconstructed image closely mirrors the ground truth. Despite every frame only having approximately one fourth of k-space sampled with a single coil, the brain could be reconstructed in detail with only the optimal transport regularization. The registered image is slightly blurry, showing potential problems with the motion field.