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Environment-aware non-rigid registration in surgery using physics-based simulation

Abstract : This paper presents a system for capturing the deformations of soft objects undergoing elastic deformations and contacts with their environment, using image and point cloud data provided by an RGB-D sensor. We improve upon previous works by integrating environment constraints in the frame-by-frame registration process. The approach combines a physics-based elastic model of the considered objects, computed in real-time using an optimized Finite Element Method (FEM), which is driven by surface constraints on the objects. Additional forces, such as gravity are added. A case study in open surgery on the liver is here described. Yet in this case a major improvement in the accuracy of the registration is provided by the integration of anatomical shape constraints, which are naturally hidden from the RGB-D camera, and that we account for through a registration with the pre-operative CT data. With a comparative study, we demonstrate the relevance of our method in a real world application mimicking an open surgery scenario where the liver has to be tracked to provide an augmented reality view.
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https://hal.archives-ouvertes.fr/hal-01930366
Contributor : Antoine Petit <>
Submitted on : Wednesday, November 21, 2018 - 7:23:39 PM
Last modification on : Wednesday, September 25, 2019 - 1:14:07 AM
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  • HAL Id : hal-01930366, version 1

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Antoine Petit, Stéphane Cotin. Environment-aware non-rigid registration in surgery using physics-based simulation. ACCV 2018 - 14th Asian Conference on Computer Vision, Dec 2018, Perth, Australia. ⟨hal-01930366⟩

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