Efficient collision detection with a deformable model of an abdominal aorta

Abstract

Nowadays, the minimally invasive virtual vascular surgery system is of particular interest. To provide realistic surgical training, collision detection plays an integral role in virtual vascular surgery. However, the blood vessel such as abdominal aorta has the characteristics of plasticity, viscoelasticity, anisotropy, inhomogeneity, and nonlinearity, which lead to complex deformation models and large-scale calculations in the collision detection process. To solve this problem, a finite-element-method based on deformation model for the abdominal aorta was provided. Then a hybrid bounding volume collision detection method, AABB-K-DOPs, was proposed to speed up the organ deformation reaction. Experimental results show that, compared with traditional methods, the proposed method accelerates real-time collision detection without affecting the accuracy.