Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties.

DANSE method enables fast reconstruction of qGRE maps with significantly reduced sensitivity to noise and magnetic field inhomogeneities. DANSE method does not require any information about field inhomogeneities during application. It exploits spatial and gradient-echo-time dependent patterns in the GRE data and previously-gained knowledge from the biophysical model, thus producing high quality qGRE maps even in the environments with high noise levels. These features along with fast computational speed can lead to broad qGRE clinical and research applications.