MRI recovery with self-calibrated denoisers without fully-sampled data

Objective Acquiring fully sampled training data is challenging for many MRI applications. We present a self-supervised image reconstruction method, termed ReSiDe, capable of recovering images solely from undersampled data. Materials and methods ReSiDe is inspired by plug-and-play (PnP) methods, but...

Ausführliche Beschreibung