Articulated Bone-Shape Cross-Parameterization and Biomechanical Visualization
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چکیده
Orthopedists invest significant amounts of effort and time trying to understand the biomechanics of articular joints and to quantify the differences occurring within a given population. While new image acquisition and processing methods currently generate richer-thanever geometry and kinematic datasets that are subject-specific, the computational and visualization tools needed to enable the comparative analysis and exploration of these datasets lag behind. In this paper we present a framework that enables the crossdataset visual exploration and analysis of articular joint biomechanics. Central to our approach is a computer-vision inspired markerless method for establishing a set of correspondences between subject-specific geometry. Manifold models are subsequently defined and deformed from one subject-specific geometry to another such that the markerless correspondences are preserved while minimizing model distortion. The resulted mutually-consistent parameterization and a variety of visualization techniques allow the users to explore the similarities and differences between datasets, and to define meaningful quantitative measures. We present results on several human wrist datasets, with applications ranging from cross-subject bone-shape analysis to surfacedetail transfer.
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