A localization framework under non-rigid deformation for robotic surgery

Abstract

In surgery, it is common to open large incisions to remove tiny tumors. Now, robotic surgery has been well recognized for high precision. However, target localization is still a challenge, owing to non-rigid deformations. Thus, we propose a precise and flexible localization framework for an MRI-compatible needle-insertion robot. We primarily address with two problems: 1) How to predict the position after deformation? 2) How to turn MRI coordinate to real-world one? Correspondingly, the primary novelty is the non-rigid position transformation model based on Thin-Plate Splines. A minor contribution lies in the data acquisition for coordinate correspondences. We validate the precision of the whole framework, and each procedure of coordinate acquisition and position transformation. It is proven that the system under our framework can predict the position with a good approximation to the target's real position. © 2011 Springer-Verlag.