Please use this identifier to cite or link to this item:
|Title:||Rapid surface registration of 3D volumes using a neural network approach||Authors:||Zhang, J.
|Issue Date:||1-Feb-2008||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||URI:||http://scholarbank.nus.edu.sg/handle/10635/51020||ISSN:||02628856||DOI:||10.1016/j.imavis.2007.04.003|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 19, 2020
WEB OF SCIENCETM
checked on Sep 11, 2020
checked on Sep 21, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.