A Unified Tensor Regression Framework for Calibrationless Dynamic, Multi-Channel MRI Reconstruction

Joshua D. Trzasko¹, Armando Manduca¹

Previously, low-rank matrix regression methods have been used to enable "calibrationless" parallel and "training-free" dynamic MRI reconstruction. In this work, we present a novel low n-rank tensor regression framework for calibrationless reconstruction of dynamic and multi-channel MRI data, and demonstrate that previously image-domain strategies arise as instances of this unifying model.