Implicit vessel surface reconstruction for visualization and CFD simulation

Abstract

Objective:

Accurate and high-quality reconstructions of vascular structures are essential for vascular disease diagnosis and blood flow simulations.These applications necessitate a trade-off between accuracy and smoothness. An additional requirement for the volume grid generation for Computational Fluid Dynamics (CFD) simulations is a high triangle quality. We propose a method that produces an accurate reconstruction of the vessel surface with satisfactory surface quality.

Methods:

A point cloud representing the vascular boundary is generated based on a segmentation result. Thin vessels are subsampled to enable an accurate reconstruction. A signed distance field is generated using Multi-level Partition of Unity Implicits and subsequently polygonized using a surface tracking approach. To guarantee a high triangle quality, the surface is remeshed.

Results:

Compared to other methods, our approach represents a good trade-off between accuracy and smoothness. For the tested data, the average surface deviation to the segmentation results is 0.19 voxel diagonals and the maximum equi-angle skewness values are below 0.75.

Conclusions:

The generated surfaces are considerably more accurate than those obtained using model-based approaches. Compared to other model-free approaches, the proposed method produces smoother results and thus better supports the perception and interpretation of the vascular topology. Moreover, the triangle quality of the generated surfaces is suitable for CFD simulations.