Dynamic guidance for robotic surgery using image-constrained biomechanical models

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Abstract

The use of physically-based models combined with image constraints for intraoperative guidance is important for surgical procedures that involve large-scale tissue deformation. A biomechanical model of tissue deformation is described in which surface positional constraints and internally generated forces are derived from endoscopic images and preoperative 4D CT data, respectively. Considering cardiac motion, a novel technique is presented which minimises the average registration error over one or more complete cycles. Features tracked in the stereo video stream provide surface constraints, and an inverse finite element simulation is presented which allows internal forces to be recovered from known preoperative displacements. The accuracy of surface texture, segmented mesh and volumetrically rendered overlays is evaluated with detailed phantom experiments. Results indicate that by combining preoperative and intraoperative images in this manner, accurate intraoperative tissue deformation modelling can be achieved. © 2010 Springer-Verlag.

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Pratt, P., Stoyanov, D., Visentini-Scarzanella, M., & Yang, G. Z. (2010). Dynamic guidance for robotic surgery using image-constrained biomechanical models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6361 LNCS, pp. 77–85). https://doi.org/10.1007/978-3-642-15705-9_10

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