Kochan, M;
Modat, M;
Vercauteren, T;
White, M;
Mancini, L;
Winston, GP;
McEvoy, AW;
... Stoyanov, D; + view all
(2016)
Bilateral Weighted Adaptive Local Similarity Measure for Registration in Neurosurgery.
In: Ourselin, S and Joskowicz, L and Sabuncu, M and Unal, G and Wells, W, (eds.)
International Conference on Medical Image Computing and Computer-Assisted Intervention MICCAI 2016: Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2016.
(pp. pp. 81-88).
Springer, Cham
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Abstract
Image-guided neurosurgery involves the display of MRI-based preoperative plans in an intraoperative reference frame. Interventional MRI (iMRI) can serve as a reference for non-rigid registration based propagation of preoperative MRI. Structural MRI images exhibit spatially varying intensity relationships, which can be captured by a local similarity measure such as the local normalized correlation coefficient (LNCC). However, LNCC weights local neighborhoods using a static spatial kernel and includes voxels from beyond a tissue or resection boundary in a neighborhood centered inside the boundary. We modify LNCC to use locally adaptive weighting inspired by bilateral filtering and evaluate it extensively in a numerical phantom study, a clinical iMRI study and a segmentation propagation study. The modified measure enables increased registration accuracy near tissue and resection boundaries.
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