As image-guided navigation plays an important role in neurosurgery, the spatial registration mapping the pre-operative images with the intra-operative patient position becomes crucial for a high accurate surgical output. Conventional landmark-based registration requires expensive and time-consuming logistic support.Surface-based registration is a plausible alternative due to its simplicity and efficacy. In this paper, we propose a comprehensive framework for surface-based registration in neurosurgical navigation, where Kinect is used to automatically acquire patient's facial surface in a real time manner. Coherent point drift(CPD) algorithm is employed to register the facial surface with pre-operative images(e.g., computed tomography(CT) or magnetic resonance imaging(MRI)) using a coarse-to-fine scheme. The spatial registration results of 6 volunteers demonstrate that the proposed framework has potential for clinical use.
Virtual reality(VR) based vascular intervention training is a fascinating innovation, which helps trainees develop skills in safety remote from patients. The vascular intervention training involves the use of flexible tipped guidewires to advance diagnostic or therapeutic catheters into a patient's vascular anatomy. In this paper, a real-time physically-based modeling approach is proposed to simulate complicated behaviors of guidewires and catheters based on Kirchhoff elastic rod. The slender body of guidewire and catheter is simulated using more efficient special case of naturally straight, isotropic Kirchhoff rods, and the short flexible tip composed of straight or angled design is modeled using more complex generalized Kirchhoff rods. We derive the equations of motion for guidewire and catheter with continuous elastic energy, and then they were discretized using a linear implicit scheme that guarantees stability and robustness. In addition, we apply a fast-projection method to enforce the inextensibility of guidewire and catheter, while an adaptive sampling algorithm is implemented to improve the simulation efficiency without reducing accuracy. Experimental results reveal that our guidewire simulation method is both robust and efficient in a real-time performance.
