Rapid surface registration of 3D volumes using a neural network approach

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-operat...

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Bibliographic Details
Published in:Image and vision computing 2008-02, Vol.26 (2), p.201-210
Main Authors: Zhang, J., Ge, Y., Ong, S.H., Chui, C.K., Teoh, S.H., Yan, C.H.
Format: Article
Language:English
Subjects:
Medical images
Neural network
Surface modelling
Surface registration
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Summary: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.
ISSN:0262-8856
1872-8138
DOI:10.1016/j.imavis.2007.04.003