… on a cardiac MRI to perform a super resolution from a 1.1 × 1.1 × 5 mm 3 to an isotropic
1.1 mm 3 resolution and to explore the visualization of myocardial scarring from cardiac LV …

… In this work, we employ deep learning algorithms combined with deformable models to …
from short-axis cardiac MRI datasets. The method employs deep learning algorithms to learn the …

… acquired SAX and four-chamber cine SSFP cardiac MRI series at 3.0 T in two healthy men
… supervision of a cardiovascular radiologist with 12 years of experience in cardiac MRI (AH). …

… of deep learning techniques to enhance its quantitative nature. This article aims to … the
concept of deep learning, review its current applications in quantitative cardiac MRI, and …

… Among the diagnostic methods, cardiac magnetic resonance imaging (CMRI) is increasingly
used … To address these issues, deep learning (DL) techniques have been employed in the …

… 482 cardiac MRI studies performed with a 1.5-T MRI system between February 2012 and
June 2017. Within these studies there were 892 LAX cine steady-state free precession series (…

Current state-of-the-art deep learning segmentation methods have not yet made a broad
entrance into the clinical setting in spite of high demand for such automatic methods. One …

… evaluation of various automatic deep learning-based methods for multi-disease, multiview,
and multi-center right ventricular segmentation in cardiac magnetic resonance imaging (CMR)…

… based retrieval of cardiac images. In this paper, we introduce a new approach based on
deep Convolutional Neural Network (CNN) to localize the LV in cardiac MRI in short axis views. …

… Cardiac Diagnosis Challenge” dataset (ACDC), the largest publicly available and fully annotated
dataset for the purpose of cardiac MRI … state-of-the-art deep learning methods can go at …