Concepts de base
The author presents CBC3D, an image-to-mesh conversion method, focusing on fidelity and quality in mesh generation for medical simulations.
Résumé
The content discusses the challenges of converting medical images into 3D meshes for simulations. It introduces CBC3D, a method that ensures high fidelity and element quality while reducing element count. The approach involves adaptive mesh generation and deformation based on energy minimization principles.
The study compares CBC3D with other industry and academia methods, highlighting its superior performance in achieving high fidelity, low element count, and good element quality. The importance of accurate geometric representation in predictive and interactive surgical simulations is emphasized. Mesh deformation techniques are detailed to align mesh surfaces with physical boundaries.
Key points include the use of Body-Centered Cubic (BCC) lattices, mixed-element meshes, and energy minimization for mesh deformation. The content also addresses segmentation algorithms, image pre-processing steps, adaptive lattice refinement, and quality control measures during mesh deformation.
CBC3D's ability to balance trade-offs between mesh size reduction and maintaining high-quality elements is a significant highlight. The study showcases the efficiency of CBC3D in generating accurate anatomical models for various medical applications.
Stats
Results indicate that the CBC3D meshes achieve high fidelity.
Element count reasonably low.
Good element quality exhibited by CBC3D meshes.