Objectives: The objective of this study was to perform a systematic review and meta-analysis
of the predictive value of late gadolinium enhancement (LGE) cardiac magnetic resonance …

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …

Manually labeling datasets with object masks is extremely time consuming. In this work, we
follow the idea of Polygon-RNN to produce polygonal annotations of objects interactively …

Manually labeling objects by tracing their boundaries is a laborious process. In Polygon-
RNN++, the authors proposed Polygon-RNN that produces polygonal annotations in a …

Differences in cardiac and aortic structure and function are associated with cardiovascular
diseases and a wide range of other types of disease. Here we analyzed cardiovascular …

Automated cardiac segmentation from magnetic resonance imaging datasets is an essential
step in the timely diagnosis and management of cardiac pathologies. We propose to tackle …

Sudden cardiac death from arrhythmia is a major cause of mortality worldwide. In this study,
we developed a novel deep learning (DL) approach that blends neural networks and …

Motivation: Integrative mathematical and statistical models of cardiac anatomy and
physiology can play a vital role in understanding cardiac disease phenotype and planning …

Multi-atlas segmentation infers the target image segmentation by combining prior
anatomical knowledge encoded in multiple atlases. It has been quite successfully applied to …

Abstract Background and Objective: Automatic cardiac segmentation plays an utmost role in
the diagnosis and quantification of cardiovascular diseases. Methods: This paper proposes …