Dynamic MRI interpolation in temporal direction using an unsupervised generative model.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

Published Date: Sep 22, 2024

Abstract

PURPOSE: Cardiac cine magnetic resonance imaging (MRI) is an important tool in assessing dynamic heart function. However, this technique requires long acquisition time and long breath holds, which presents difficulties. The aim of this study is to propose an unsupervised neural network framework that can perform cardiac cine interpolation in time, so that we can increase the temporal resolution of cardiac cine without increasing acquisition time.

Authors

Corbin Maciel

Department of Biomedical Engineering, University of Texas Southwestern Medical Center, Dallas, USA.
Qing Zou

Division of Pediatric Cardiology, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, USA.

Keywords

Algorithms Heart Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging, Cine Neural Networks, Computer Unsupervised Machine Learning

External Resources

View on PubMed Access via DOI PubMed (39326176)

Dynamic MRI interpolation in temporal direction using an unsupervised generative model.

Abstract

Authors

Keywords

External Resources

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