Matthias Schloegl1, Florian Knoll1, Katharina Gruber1, Franz Ebner2, Rudolf Stollberger1
1Institute for medical Engineering, TU Graz, Graz, Austria; 2Universittsklinik fr Radiologie, Medizinische Universitt Graz, Graz, Austria
This study investigates about the capability of image metrics as objective tool for quality evaluation of non-linear reconstruction methods in the context of compressed sensing. Metric rating of reconstructions with TGV, IRGN-TV, l1-SPIRiT and CGSENSE with Cartesian, radial and random sub-sampled trajectories was compared to that of six experienced radiologists, focusing on overall image quality and recognizability of anatomy and pathology. Datasets from several body regions affected by identified pathologies were selected. Good correlations were found for metrics based upon models of the human visual system as well as for common image metrics when calculated for a region of interest.