Please use this identifier to cite or link to this item:
|Title:||Multimodal image registration system for image-guided orthopaedic surgery||Authors:||Zhang, J.
Level set method
Multimodality image fusion
|Issue Date:||Sep-2011||Citation:||Zhang, J., Yan, C.H., Chui, C.K., Ong, S.H., Wang, S.C. (2011-09). Multimodal image registration system for image-guided orthopaedic surgery. Machine Vision and Applications 22 (5) : 851-863. ScholarBank@NUS Repository. https://doi.org/10.1007/s00138-010-0302-z||Abstract:||We present a novel multimodality image registration system for spinal surgery. The system comprises a surface-based algorithm that performs computed tomography/magnetic resonance (CT/MR) rigid registration and MR image segmentation in an iterative manner. The segmentation/registration process progressively refines the result of MR image segmentation and CT/MR registration. For MR image segmentation, we propose a method based on the double-front level set that avoids boundary leakages, prevents interference from other objects in the image, and reduces computational time by constraining the search space. In order to reduce the registration error from the misclassification of the soft tissue surrounding the bone in MR images, we propose a weighted surface-based CT/MR registration scheme. The resultant weighted surface is registered to the segmented surface of the CT image. Contours are generated from the reconstructedCTsurfaces for subsequentMRimage segmentation. This process iterates till convergence. The registration method achieves accuracy comparable to conventional techniques while being significantly faster. Experimental results demonstrate the advantages of the proposed approach and its application to different anatomies. © Springer-Verlag 2010.||Source Title:||Machine Vision and Applications||URI:||http://scholarbank.nus.edu.sg/handle/10635/50986||ISSN:||09328092||DOI:||10.1007/s00138-010-0302-z|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 29, 2020
checked on Sep 21, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.