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|Title:||Rapid surface registration of 3D volumes using a neural network approach|
|Authors:||Zhang, J. |
|Citation:||Zhang, J., Ge, Y., Ong, S.H., Chui, C.K., Teoh, S.H., Yan, C.H. (2008-02-01). Rapid surface registration of 3D volumes using a neural network approach. Image and Vision Computing 26 (2) : 201-210. ScholarBank@NUS Repository. https://doi.org/10.1016/j.imavis.2007.04.003|
|Abstract:||An automatic surface-based rigid registration system using a neural network representation is proposed. The system has been applied to register human bone structures for image-guided surgery. A multilayer perceptron neural network is used to construct a patient-specific surface model from pre-operative images. A surface representation function derived from the resultant neural network model is then employed for intra-operative registration. The optimal transformation parameters are obtained via an optimization process. This segmentation/registration system achieves sub-voxel accuracy comparable to that of conventional techniques, and is significantly faster. These advantages are demonstrated using image datasets of the calcaneus and vertebrae. © 2007 Elsevier B.V. All rights reserved.|
|Source Title:||Image and Vision Computing|
|Appears in Collections:||Staff Publications|
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