Global registration of multiple point sets: feasibility and applications in multi-fragment fracture fixation
An algorithm to globally register multiple 3D data sets (point sets) within a general reference frame is proposed. The algorithm uses the Unscented Kalman Filter algorithm to simultaneously compute the registration transformations that map the data sets together, and to calculate the variances of th...
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| Vydáno v: | Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Ročník 10; číslo Pt 2; s. 943 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
01.01.2007
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| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Shrnutí: | An algorithm to globally register multiple 3D data sets (point sets) within a general reference frame is proposed. The algorithm uses the Unscented Kalman Filter algorithm to simultaneously compute the registration transformations that map the data sets together, and to calculate the variances of the registration parameters. The data sets are either randomly generated, or collected from a set of fractured bone phantoms using Computed Tomography (CT) images. The algorithm robustly converges for isotropic Gaussian noise that could have perturbed the point coordinates in the data sets. It is also computationally efficient, and enables real-time global registration of multiple data sets, with applications in computer-assisted orthopaedic trauma surgery.An algorithm to globally register multiple 3D data sets (point sets) within a general reference frame is proposed. The algorithm uses the Unscented Kalman Filter algorithm to simultaneously compute the registration transformations that map the data sets together, and to calculate the variances of the registration parameters. The data sets are either randomly generated, or collected from a set of fractured bone phantoms using Computed Tomography (CT) images. The algorithm robustly converges for isotropic Gaussian noise that could have perturbed the point coordinates in the data sets. It is also computationally efficient, and enables real-time global registration of multiple data sets, with applications in computer-assisted orthopaedic trauma surgery. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| DOI: | 10.1007/978-3-540-75759-7_114 |