Model-updated Image-guided Liver Surgery: Preliminary results using Intra-operative surface characterization

The current protocol for image-guidance in liver surgeries involves rigid registration algorithm. Systematic studies have shown that the liver can deform up to 2cms during surgeries thereby compromising the accuracy of the surgical navigation systems. Compensating for intraoperative deformations using computational models has shown promising results. In this work, we follow up the initial rigid registration with a computational approach. The proposed computational approach relies on the closest point distances between the undeformed pre-operative surface and the rigidly registered deformed intra-operative surface. We also introduce a spatial smoothing filter to generate a realistic deformation field using the closest point distances. The proposed approach was validated in both phantom experiments and clinical cases. Preliminary results are encouraging and suggest that computational models can be used to improve the accuracy of image-guided liver surgeries.