A deep learning approach for synthetic MRI based on two routine sequences and training with synthetic data.
Journal:
Computer methods and programs in biomedicine
Published Date:
Aug 31, 2021
Abstract
BACKGROUND AND OBJECTIVE: Synthetic magnetic resonance imaging (MRI) is a low cost procedure that serves as a bridge between qualitative and quantitative MRI. However, the proposed methods require very specific sequences or private protocols which have scarcely found integration in clinical scanners. We propose a learning-based approach to compute T1, T2, and PD parametric maps from only a pair of T1- and T2-weighted images customarily acquired in the clinical routine.
