ABSTRACT
BACKGROUND: Augmented reality (AR) allows the surgeon to represent holographic patient-specific anatomical information and surgical instruments in the physical world. To correctly superimpose virtual and physical objects, a hand-eye (HE) calibration method for mapping the virtual and physical spaces was proposed. METHODS: Mathematical relationships between the virtual camera and the physical space were derived. Finally, the accuracy and robustness of the proposed HE calibration method were qualitatively and quantitatively evaluated. RESULTS: The proposed calibration method allows us to determine an optimal invariant spatiotemporal mapping between the virtual camera and the physical space. CONCLUSION: Qualitatively and quantitatively reliable and accurate estimates for the physical-virtual mapping transformation were verified. Consequently, imaging data and surgical instruments holograms can be precisely represented in the physical space.
Subject(s)
Orthopedic Procedures/methods , Surgery, Computer-Assisted/methods , Calibration , Humans , Male , Reproducibility of ResultsABSTRACT
Anatomic hepatectomies are resections in which compromised segments or sectors of the liver are extracted according to the topological structure of its vascular elements. Such structure varies considerably among patients, which makes the current anatomy-based planning methods often inaccurate. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D. The method is based on standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.
