Abstract #0873

Simultaneous multi-modality/multi-contrast image reconstruction with nuclear-norm TGV

Florian Knoll¹, Martin Holler², Thomas Koesters¹, Martijn Cloos¹, Ricardo Otazo¹, Kristian Bredies², and Daniel K Sodickson¹

¹Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States, ²Mathematics and Scientific Computing, University of Graz, Graz, Austria

A typical clinical imaging protocol covers a large number of different image contrasts and, in the era of multi-modality systems, even different imaging modalities. While the resulting datasets share a substantial amount of structural information, they consist of fundamentally different contrasts and signal values and show unique features and image content. We propose a reconstruction framework based on nuclear-norm second-order Total Generalized Variation that exploits structural similarity both between different contrasts and modalities while still being flexible with respect to signal intensity and unique features. Numerical simulations and in vivo MR-Fingerprinting experiments demonstrate improved PET resolution and improved depiction of quantitative values. The proposed approach allows a 6 minute whole brain coverage exam that provides both quantitative PET and MR-relaxation parameters.

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