Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease.
Journal:
Magnetic resonance in medicine
Published Date:
Sep 8, 2018
Abstract
PURPOSE: Real-time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability of CNNs to reconstruct highly accelerated radial real-time data in patients with congenital heart disease (CHD).
Authors
Keywords
Adolescent
Adult
Algorithms
Artifacts
Breath Holding
Cardiac-Gated Imaging Techniques
Deep Learning
Fourier Analysis
Heart
Heart Defects, Congenital
Humans
Image Interpretation, Computer-Assisted
Image Processing, Computer-Assisted
Magnetic Resonance Imaging, Cine
Male
Middle Aged
Respiration
Retrospective Studies
Young Adult