Cardiac Motion Modeling with Parallel Transport and Shape Splines
This work addresses cardiac function analysis in disease cases, but it is incremental as it applies existing frameworks to a specific medical domain.
The paper tackled the problem of modeling cardiac motion in the right ventricle under disease conditions by using LDDMM, parallel transport, and shape splines to estimate and normalize deformations, finding significant differences in model parameters across 314 patients with various pathologies.
In cases of pressure or volume overload, probing cardiac function may be difficult because of the interactions between shape and deformations.In this work, we use the LDDMM framework and parallel transport to estimate and reorient deformations of the right ventricle. We then propose a normalization procedure for the amplitude of the deformation, and a second-order spline model to represent the full cardiac contraction. The method is applied to 3D meshes of the right ventricle extracted from echocardiographic sequences of 314 patients divided into three disease categories and a control group. We find significant differences between pathologies in the model parameters, revealing insights into the dynamics of each disease.