Deep Learning‐Based Dynamic Segmentation of the Left Atrium in 4D Flow MRI
ABSTRACT Purpose To design a deep learning pipeline for automated, time‐resolved segmentation of the left atrium (LA) from 4D flow MRI data. Methods We studied 100 individuals including 65 patients with atrial fibrillation (AF) and 35 healthy subjects (HS) resulting in 2530 4D flow MRI time‐volumes acquired in different centers and scanners.
Jonas Leite +16 more
wiley +1 more source
Dosimetric characteristics of cardiorespiratory motion during cardiac stereotactic body radiotherapy and dose gain from respiratory gating. [PDF]
Wang G +11 more
europepmc +1 more source
“Two‐For‐One”: 4D Cardiac and Pulmonary MR Imaging From a Single Acquisition Using bSTAR
ABSTRACT Purpose To generate 4D (3D+time) images of both the heart and lungs using a single volumetric radial free‐breathing bSSFP dual echo acquisition (bSTAR) with two image reconstructions within a single pipeline deployed inline at 0.55 and 1.5 T.
Pierre Daudé +9 more
wiley +1 more source
Experimental Platform for Screening and Validation of BacNa<sub>v</sub> Gene Therapy Candidates. [PDF]
Wu T, Nguyen HX, Siu YY, Li Y, Bursac N.
europepmc +1 more source
ABSTRACT Purpose To develop a unified image reconstruction framework that bridges real‐time and gated cardiac MRI, including quantitative MRI. Methods We introduce generative multitasking, which learns subject‐ and dataset‐specific implicit neural temporal bases from sequence timings and an interpretable latent space for cardiac and respiratory motion.
Xinguo Fang, Anthony G. Christodoulou
wiley +1 more source
Cinematic rendering-enhanced computed tomography of right intracardiac thrombi: A case report. [PDF]
Lugo-Fagundo E +3 more
europepmc +1 more source
Flow 2.0: A Standardized Toolbox for Real‐Time Phase‐Contrast MRI of Neurofluid Dynamics
ABSTRACT Purpose Real‐time phase‐contrast MRI (RT‐PC) enables continuous quantification of physiological flow dynamics across multiple temporal frequencies, but its broader application is limited by complex and fragmented post‐processing workflows.
Pan Liu, Olivier Balédent
wiley +1 more source
Gut microbiota alters cardiac metabolism and immune system composition in viral myocarditis mice. [PDF]
Chen L, Wu W, Kong Q.
europepmc +1 more source
[Gating kinetics of the cardiac Na+ channel].
Mitsuiye, Tamotsu, Noma, Akinori
openaire +2 more sources
Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals
ABSTRACT Purpose To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR training datasets.
Anirudh Raman +10 more
wiley +1 more source

