Global registration of ultrasound to MRI using the LC2 metric for enabling neurosurgical guidance
Wein W, Ladikos A, Fuerst B, Shah A, Sharma K, Navab N (2013)
Publication Type: Conference contribution
Publication year: 2013
Journal
Book Volume: 8149 LNCS
Pages Range: 34-41
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: JPN
ISBN: 9783642408106
DOI: 10.1007/978-3-642-40811-3_5
Abstract
Automatic and robust registration of pre-operative magnetic resonance imaging (MRI) and intra-operative ultrasound (US) is essential to neurosurgery. We reformulate and extend an approach which uses a Linear Correlation of Linear Combination (LC2)-based similarity metric, yielding a novel algorithm which allows for fully automatic US-MRI registration in the matter of seconds. It is invariant with respect to the unknown and locally varying relationship between US image intensities and both MRI intensity and its gradient. The overall method based on this both recovers global rigid alignment, as well as the parameters of a free-form-deformation (FFD) model. The algorithm is evaluated on 14 clinical neurosurgical cases with tumors, with an average landmark-based error of 2.52mm for the rigid transformation. In addition, we systematically study the accuracy, precision, and capture range of the algorithm, as well as its sensitivity to different choices of parameters. © 2013 Springer-Verlag.
Involved external institutions
Germany (DE)How to cite
APA:
Wein, W., Ladikos, A., Fuerst, B., Shah, A., Sharma, K., & Navab, N. (2013). Global registration of ultrasound to MRI using the LC2 metric for enabling neurosurgical guidance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 34-41). JPN.
MLA:
Wein, Wolfgang, et al. "Global registration of ultrasound to MRI using the LC2 metric for enabling neurosurgical guidance." Proceedings of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, JPN 2013. 34-41.
BibTeX: Download