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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Bilateral Weighted Adaptive Local Similarity Measure for Registration in Neurosurgery
verfasst von : Martin Kochan, Marc Modat, Tom Vercauteren, Mark White, Laura Mancini, Gavin P. Winston, Andrew W. McEvoy, John S. Thornton, Tarek Yousry, John S. Duncan, Sébastien Ourselin, Danail Stoyanov
Erschienen in: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016
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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.