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Fully Automated Quantification of the Myocardium and Scar Volumes in Hypertrophic Cardiomyopathy Using Three-Dimensional Deep Convolutional Neural Networks

Fahmy, AS, Marcel Beetz, Ulf Neisius, RH Chan, MS Maron, Evan Appelbaum, Menze, and Reza Nezafat. 2019. “Fully Automated Quantification of the Myocardium and Scar Volumes in Hypertrophic Cardiomyopathy Using Three-Dimensional Deep Convolutional Neural Networks”. In: Proceedings from the 22nd Annual Society for Cardiovascular Magnetic Resonance (SCMR) Scientific Sessions, Bellevue, WA.

Association of Local Conduction Velocity with Late Gadolinium Enhancement and Myocardial Wall Thickness on Cardiac Magnetic Resonance in Swine Model of Left Ventricular Post-infarction

Jang, Jihye, John Whitaker, Leshem, Long Ngo, Shiro Nakamori, WJ Manning, Elad Anter, and Reza Nezafat. 2019. “Association of Local Conduction Velocity With Late Gadolinium Enhancement and Myocardial Wall Thickness on Cardiac Magnetic Resonance in Swine Model of Left Ventricular Post-Infarction”. In: Proceedings from the 22nd Annual Society for Cardiovascular Magnetic Resonance (SCMR) Scientific Sessions, Bellevue, WA.

Non-Contrast Scar Assessment using Radiomics: Texture Analysis of Native T1 images in Hypertrophic Cardiomyopathy

Neisius, Ulf, Hossam El-Rewaidy, Shiro Nakamori, Jennifer Rodriguez, WJ Manning, and Reza Nezafat. 2019. “Non-Contrast Scar Assessment Using Radiomics: Texture Analysis of Native T1 Images in Hypertrophic Cardiomyopathy”. In: Proceedings from the 22nd Annual Society for Cardiovascular Magnetic Resonance (SCMR) Scientific Sessions, Bellevue, WA.

Incremental Role of Left Atrial and Right Ventricular Strains for Predicting Cardiovascular Outcome in Heart Failure Preserved Ejection Fraction Patients: A Machine Learning Approach

Kucukseymen, Selcuk, Arghavan Arafati, Talal Al-Otaibi, Hossam El-Rewaidy, WJ Manning, and Reza Nezafat. 2021. “Incremental Role of Left Atrial and Right Ventricular Strains for Predicting Cardiovascular Outcome in Heart Failure Preserved Ejection Fraction Patients: A Machine Learning Approach”. Journal of the American College of Cardiology 77 (18): 1268.