Improving MR image quality with a multi-task model, using convolutional losses
Abstract Purpose During the acquisition of MRI data, patient-, sequence-, or hardware-related factors can introduce artefacts that degrade image quality.Four of the most significant tasks for improving MRI image quality have been bias field correction, super-resolution, motion-, and noise correction.Machine learning has achieved outstanding results