Evaluation of a New 3D/2D Registration Criterion for Liver Radio-Frequencies Guided by Augmented Reality

Our purpose in this article is to superimpose a 3D model of the liver, its vessels and tumors (reconstructed from CT images) on external video images of the patient for hepatic surgery guidance. The main constraints are the robustness, the accuracy and the computation time. Because of the absence of visible anatomical landmarks and of the "cylindrical" shape of the upper abdomen, we used some radio-opaque fiducials. The classical least-squares method assuming that there is no noise on the 3D point positions, we designed a new Maximum Likelihood approach to account for this existing noise and we show that it generalizes the classical approaches. Experiments on synthetic data provide evidences that our new criterion is up to 20% more accurate and much more robust, while keeping a computation time compatible with realtime at 20 to 40 Hz. Eventually, careful validation experiments on real data show that an accuracy of 2 mm can be achieved within the liver.