to different subject meshes M, we are locating two anatomical landmark points on their corresponding base meshes S. As cardiac landmarks we use the apex and the mid-septal point of…
Fig. 1. Pipeline of the proposed method: (a) ambient space with M input features for each subject, (b) feature-specific and global affinity matrices used as input to the MKL optimization,…
Fig. 1. Geometrical models with color coded activation times resulting from the electrophysiological simulation. 2.2 Electrophysiological Modeling The ion kinetics at each of the voxels representing atrial myocytes were computed…
Fig. 1. Three components for an in-vivo assessment tool are pre-strain measurement, inverse model and population average fiber architecture of valve leaflets 2 Methods To demonstrate the ideal capabilities of…
regularization, which induces sparsity, in our integration method. We also introduce regularization to make the dense fields more adhering to cardiac biomechanics. Finally, we motivate the necessity of temporal coherence…
Fig. 1. Exemplary cardiac phases of CP-BOLD MR (top row) and standard CINE MR (bottom row) obtained from the same subject under baseline conditions (absence of ischemia) where the myocardium…
Fig. 1. Primary eigenvectors of the diffusion tensors in the left ventricle (LV) colour-coded by (a) their derived fibre angles showing discontinuities in spatial variation, and (b) fractional anisotropy (FA)…
and capture the whole volume of the isolated heart (approx. 112 cm). 2.2 Data Preprocessing Slicewise segmentation and labeling was performed by visual inspection, discriminating the left and right ventricle…
norm [3] and norm [4] of partial field derivatives; using complex-valued random Markov field [5] and using regularizing conditions [6]. The aim of this work is to compare graph-cut and…
Fig. 1. CircAdapt model representation (left) with aorta and aortic valve parameters (right). RA: right atrium, LA: left atrium, RV: right ventricle, LV: left ventricle, TV: tricuspid valve, PV: pulmonary valve,…
