AIMC Topic: Ventricular Function
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Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.
Magnetic resonance imaging
Dec 19, 2024
OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine images can be collected post-contrast to minimize non-scanning time prior to late gadolinium-enhanced imaging. This study aimed to assess the equivalency o...
Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population; a common mistake.
The international journal of cardiovascular imaging
Feb 24, 2023
Reliability (repeatability or agreement) is assessed by different statistical tests including Pearson r or Spearman rho which is one of the common mistakes in reliability analysis. Pearson r or Spearman rho correlation coefficient only assesses the l...
Fast and robust parameter estimation with uncertainty quantification for the cardiac function.
Computer methods and programs in biomedicine
Feb 4, 2023
BACKGROUND AND OBJECTIVES: Parameter estimation and uncertainty quantification are crucial in computational cardiology, as they enable the construction of digital twins that faithfully replicate the behavior of physical patients. Many model parameter...
Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population.
The international journal of cardiovascular imaging
Jan 17, 2023
This study aimed to assess the image quality and accuracy of respiratory-gated real-time two-dimensional (2D) cine incorporating deep learning reconstruction (DLR) for the quantification of biventricular volumes and function compared with those of th...
Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imaging.
Scientific reports
Apr 22, 2022
Cardiovascular magnetic resonance imaging is the gold standard for cardiac function assessment. Quantification of clinical results (CR) requires precise segmentation. Clinicians statistically compare CRs to ensure reproducibility. Convolutional Neura...
Deep Learning-based Method for Fully Automatic Quantification of Left Ventricle Function from Cine MR Images: A Multivendor, Multicenter Study.
Radiology
Oct 9, 2018
Purpose To develop a deep learning-based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods This r...
Machine learning for predictive analytics in medicine: real opportunity or overblown hype?
European heart journal. Cardiovascular Imaging
Jul 1, 2018
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