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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zikic, D. Kamen, A. Navab, N. |
| Copyright Year | 2010 |
| Description | Author affiliation: Siemens Corporate Research (SCR), Princeton, NJ, USA (Kamen, A.) || Computer Aided Medical Procedures (CAMP), Technische Universita¨t Mu¨nchen, Germany (Zikic, D.; Navab, N.) |
| Abstract | We apply the concept of natural gradients to deformable registration. The motivation stems from the lack of physical interpretation for gradients of image-based difference measures. The main idea is to endow the space of deformations with a distance metric which reflects the variation of the difference measure between two deformations. This is in contrast to standard approaches which assume the Euclidean frame. The modification of the distance metric is realized by treating the deformations as a Riemannian manifold. In our case, the manifold is induced by the Riemannian metric tensor based on the approximation of the Fisher Information matrix, which takes into account the information about the chosen difference measure and the input images. Thus, the resulting natural gradient defined on this manifold inherently takes into account this information. The practical advantages of the proposed approach are the improvement of registration error and faster convergence for low-gradient regions. The proposed scheme is applicable to arbitrary difference measures and can be readily integrated into standard variational deformable registration methods with practically no computational overhead. |
| Starting Page | 2847 |
| Ending Page | 2854 |
| File Size | 684157 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424469840 |
| ISSN | 10636919 |
| e-ISBN | 9781424469857 |
| DOI | 10.1109/CVPR.2010.5540019 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Tensile stress Convergence Distortion measurement Stochastic processes Erbium Biomedical imaging Thyristors Measurement standards Impedance Euclidean distance |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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