Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.imavis.2007.04.003
Title: Rapid surface registration of 3D volumes using a neural network approach
Authors: Zhang, J. 
Ge, Y.
Ong, S.H. 
Chui, C.K. 
Teoh, S.H. 
Yan, C.H. 
Keywords: Medical images
Neural network
Surface modelling
Surface registration
Issue Date: 1-Feb-2008
Source: 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
URI: http://scholarbank.nus.edu.sg/handle/10635/51020
ISSN: 02628856
DOI: 10.1016/j.imavis.2007.04.003
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