Left atrial adaptation in ischemic heart disease: insights from a cardiovascular magnetic resonance study.

Left atrium (LA) plays a key role in the overall cardiac performance. However, it remains unclear how LA adapts, in terms of function and volumes, to left ventricular dysfunction in the acute and post-acute phases of myocardial infarction. LA volumes and function were evaluated in patients in the acute phase of ST-segment elevation myocardial infarction (acute-STEMI group) and in the post-acute phase after STEMI (post-acute STEMI group).

On Linear Spaces of Polyhedral Meshes.

Polyhedral meshes (PM)-meshes having planar faces-have enjoyed a rise in popularity in recent years due to their importance in architectural and industrial design. However, they are also notoriously difficult to generate and manipulate. Previous methods start with a smooth surface and then apply elaborate meshing schemes to create polyhedral meshes approximating the surface.

Smooth Rotation Enhanced As-Rigid-As-Possible Mesh Animation.

In recent years, the As-Rigid-As-Possible (ARAP) shape deformation and shape interpolation techniques gained popularity, and the ARAP energy was successfully used in other applications as well. We improve the ARAP animation technique in two aspects. First, we introduce a new ARAP-type energy, named SR-ARAP, which has a consistent discretization for surfaces (triangle meshes).

Single breath-hold 3D measurement of left atrial volume using compressed sensing cardiovascular magnetic resonance and a non-model-based reconstruction approach.

Background: Left atrial (LA) dilatation is associated with a large variety of cardiac diseases. Current cardiovascular magnetic resonance (CMR) strategies to measure LA volumes are based on multi-breath-hold multi-slice acquisitions, which are time-consuming and susceptible to misregistration.

Aim: To develop a time-efficient single breath-hold 3D CMR acquisition and reconstruction method to precisely measure LA volumes and function.

D-Snake: Image Registration by As-Similar-As-Possible Template Deformation.

We describe a snake-type method for shape registration in 2D and 3D, by fitting a given polygonal template to an acquired image or volume data. The snake aspires to fit itself to the data in a shape which is locally As-Similar-As-Possible (ASAP) to the template. Our ASAP regulating force is based on the Moving Least Squares (MLS) similarity deformation.