Seeing Between Time: Higher Frame Rate Cardiac Cine MRI Using Deep Learning
Overview
Overview
Journal
Radiol Cardiothorac Imaging
Specialty
Cardiology & Vascular Diseases
Date
2024 Jun 6
PMID
38842457
Authors
Authors
Affiliations
Affiliations
Soon will be listed here.
References
1.
van Hateren J
. Spatiotemporal contrast sensitivity of early vision. Vision Res. 1993; 33(2):257-67.
DOI: 10.1016/0042-6989(93)90163-q.
View
2.
Marcus E, Teuwen J
. Artificial intelligence and explanation: How, why, and when to explain black boxes. Eur J Radiol. 2024; 173:111393.
DOI: 10.1016/j.ejrad.2024.111393.
View
3.
Morales M, Ghanbari F, Nakamori S, Assana S, Amyar A, Yoon S
. Deformation-encoding Deep Learning Transformer for High-Frame-Rate Cardiac Cine MRI. Radiol Cardiothorac Imaging. 2024; 6(3):e230177.
PMC: 11211941.
DOI: 10.1148/ryct.230177.
View
4.
Atkinson D, Edelman R
. Cineangiography of the heart in a single breath hold with a segmented turboFLASH sequence. Radiology. 1991; 178(2):357-60.
DOI: 10.1148/radiology.178.2.1987592.
View
5.
Schmidt-Rimpler J, Backhaus S, Hartmann F, Schaten P, Lange T, Evertz R
. Impact of temporal and spatial resolution on atrial feature tracking cardiovascular magnetic resonance imaging. Int J Cardiol. 2023; 396:131563.
DOI: 10.1016/j.ijcard.2023.131563.
View