Berk Tınaz

Semi-Supervised Learning of Mutually Accelerated Multi-Contrast MRI Synthesis without Fully-Sampled Ground-Truths.

2020

This study proposes a novel semi-supervised learning framework for mutually accelerated multi-contrast MRI synthesis that recovers high-quality images without demanding large training sets of costly fully-sampled source or ground-truth target images. The proposed method presents …