Rigid registration of untracked freehand 2D ultrasound sweeps to 3D CT of liver tumours
Cifor A, Risser L, Heinrich MP, Chung D, Schnabel JA (2013)
Publication Type: Conference contribution
Publication year: 2013
Journal
Book Volume: 8198 LNCS
Pages Range: 155-164
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: JPN
ISBN: 9783642410826
DOI: 10.1007/978-3-642-41083-3_18
Abstract
We present a rigid registration framework for freehand 2D ultrasound sweeps to 3D CT of liver tumours. The method registers the 2D sweeps in a group-wise manner, without the need for prior 3D ultrasound compounding or probe tracking during acquisition. We first introduce a specific acquisition model to keep the dimension of this problem reasonable. Only seven parameters are indeed required to register the images. These are estimated using simulated annealing optimization of a robust modality-independent similarity measure. The framework contrasts the current methods that rely on tracking devices and phantom calibration, which are often difficult to use routinely in clinical practice. Our results on both synthetic and real data show that the method is well-suited for such ultrasound-CT registration of liver tumours. © 2013 Springer-Verlag.
Involved external institutions
United Kingdom (GB)
France (FR)How to cite
APA:
Cifor, A., Risser, L., Heinrich, M.P., Chung, D., & Schnabel, J.A. (2013). Rigid registration of untracked freehand 2D ultrasound sweeps to 3D CT of liver tumours. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 155-164). JPN.
MLA:
Cifor, Amalia, et al. "Rigid registration of untracked freehand 2D ultrasound sweeps to 3D CT of liver tumours." Proceedings of the 5th International Workshop on Abdominal Imaging: Computation and Clinical Applications, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, JPN 2013. 155-164.
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