Whole heart segmentation from magnetic resonance imaging or computed tomography is a
prerequisite for many clinical applications. Since manual delineation can be tedious and …

While deep convolutional neural networks (CNNs) have achieved remarkable success in 2D
medical image segmentation, it is still a difficult task for CNNs to segment important organs …

Background Preservation and improvement of heart and vessel health is the primary
motivation behind cardiovascular disease (CVD) research. Development of advanced …

Abstract Magnetic Resonance Imaging (MRI), a reference examination for cardiac
morphology and function in humans, allows to image the cardiac right ventricle (RV) with …

Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance,
fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic …

Electromechanical (EM) models of the heart have been used successfully to study
fundamental mechanisms underlying a heart beat in health and disease. However, in all …

Recently, model-based methods for the automatic segmentation of the heart chambers have
been proposed. An important application of these methods is the characterization of the …

Robotic intra-operative ultrasound has the potential to improve the conventional practice of
diagnosis and procedure guidance that are currently performed manually. Working towards …

Segmenting ventricular structures from cardiovascular MR scan is important for quantitative
evaluation of heart. Manual delineation is time-consuming and tedious and lack of …

CT and MR are dominant imaging modalities in cardiovascular inspection. Segmenting the
whole heart from CT and MR volumes, and parsing it into distinctive substructures are highly …