Towards realtime multimodal fusion for image-guided interventions using self-similarities
Heinrich MP, Jenkinson M, Papiez BW, Brady SM, Schnabel JA (2013)
Publication Type: Conference contribution
Publication year: 2013
Journal
Book Volume: 8149 LNCS
Pages Range: 187-194
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_24
Abstract
Image-guided interventions often rely on deformable multi-modal registration to align pre-treatment and intra-operative scans. There are a number of requirements for automated image registration for this task, such as a robust similarity metric for scans of different modalities with different noise distributions and contrast, an efficient optimisation of the cost function to enable fast registration for this time-sensitive application, and an insensitive choice of registration parameters to avoid delays in practical clinical use. In this work, we build upon the concept of structural image representation for multi-modal similarity. Discriminative descriptors are densely extracted for the multi-modal scans based on the "self-similarity context". An efficient quantised representation is derived that enables very fast computation of point-wise distances between descriptors. A symmetric multi-scale discrete optimisation with diffusion regularisation is used to find smooth transformations. The method is evaluated for the registration of 3D ultrasound and MRI brain scans for neurosurgery and demonstrates a significantly reduced registration error (on average 2.1 mm) compared to commonly used similarity metrics and computation times of less than 30 seconds per 3D registration. © 2013 Springer-Verlag.
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United Kingdom (GB)How to cite
APA:
Heinrich, M.P., Jenkinson, M., Papiez, B.W., Brady, S.M., & Schnabel, J.A. (2013). Towards realtime multimodal fusion for image-guided interventions using self-similarities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 187-194). JPN.
MLA:
Heinrich, Mattias Paul, et al. "Towards realtime multimodal fusion for image-guided interventions using self-similarities." Proceedings of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, JPN 2013. 187-194.
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