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Introduction

CPU. Segmentation. Creation of FE model. Implant Update. Multigrid Solver. Chair for . Computer Graphics and Visualization. Acquisition. Voxelization. Stress Visualization. CT Scanner. GPU. Computer Graphics. and Visualization. Biomedicine. Computational Steering

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Introduction

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  1. CPU Segmentation Creationof FE model Implant Update Multigrid Solver Chair for Computer Graphics and Visualization Acquisition Voxelization Stress Visualization CT Scanner GPU Computer Graphics and Visualization Biomedicine Computational Steering for Patient-Specific Implant Planning in Orthopedics Introduction Fast and reliable methods for predicting and monitoring in-vivo bone strength are of great importance for hip joint replacement. To avoid adaptive remodeling with cortical thinning and increased porosity of the bone due to stress shielding, in a preoperative planning process the optimal implant design, size, and position has to be determined. This process involves interactive implant positioning within the bone as well as simulation and visualization of the stress within bone and implant due to exerting forces. In this paper, we present a prototype of such a visual analysis tool, which, to our best knowledge, provides the first computational steering environment for optimal implant selection and positioning. This prototype considers patient-specific biomechanical properties of the bone to select the optimal implant design, size, and position according to the prediction of individual load transfer from the implant to the bone. Methods • Our model is based on linear elasticity using heterogeneous material properties described by the Young’s modulus E. We also assume the material to be isotropic, which is a common abstraction from the real bone behavior due to the difficulty in identifying the anisotropic material parameters. • We have developed a fast and stable multigrid finite-element solver for hexahedral elements, which enables interactive simulation of the stress distribution within the bone and the implant. • By utilizing a real-time GPU-method to detect elements that are covered by the moving implant, we can automatically generate computational models from patient-specific CT scans in real-time, and we can instantly feed these models into the simulation process. • Hardware-accelerated volume ray-casting, which is extended by a new method to accurately visualize sub-hexahedron implant boundaries, provides a new quality of orthopedic surgery planning. Screenshot of the simulation environment. Overview of the proposed surgery support system. Results We give a detailed analysis of the presented surgery support system. Below, we show the visualization of the stress distribution inside the bone at different FE model resolutions, without and with the implant. Note that the principal stress distribution can already be deduced from the coarsest resolution. Timing statistics of the surgery support system (Intel Core2 Quad desktop PC). 8x8x8 CT voxels / hexahedron 4x4x4 CT voxels / hexahedron 2x2x2 CT voxels / hexahedron Technische Universität München Department of Computer Science

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