@inproceedings{ Kochan2016Bilateral,

year={ 2016 },

booktitle={ Medical Image Computing and Computer Assisted Intervention },

title={ Bilateral Weighted Adaptive Local Similarity Measure for Registration in Neurosurgery },

keywords={ Non-rigid Registration; Similarity Measure; Neurosurgery; },

author={ Kochan, Martin; Modat, Marc; Vercauteren, Tom; White, Mark; Mancini, Laura; Winston, Gavin; McEvoy, Andrew; Thornton, John; Yousry, Tarek; Duncan, John S.; Ourselin, Sebastien; Stoyanov, Danail; },

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. }