  Calcification has significant influence over cardiovascular diseases and
interventions. Detailed characterization of calcification is thus desired for
predictive modeling, but calcified heart meshes for physics-driven simulations
are still often reconstructed using manual operations. This poses a major
bottleneck for large-scale adoption of computational simulations for research
or clinical use. To address this, we propose an end-to-end automated meshing
algorithm that enables robust incorporation of patient-specific calcification
onto a given heart mesh. The algorithm provides a substantial speed-up from
several hours of manual meshing to $\sim$1 minute of automated computation, and
it solves an important problem that cannot be addressed with recent template
registration-based heart meshing techniques. We validated our final calcified
heart meshes with extensive simulations, demonstrating our ability to
accurately model patient-specific aortic stenosis and Transcatheter Aortic
Valve Replacement. Our method may serve as an important tool for accelerating
the development and usage of physics-driven simulations for cardiac digital
twins.
