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Publication Detail
Bilateral Weighted Adaptive Local Similarity Measure for Registration in Neurosurgery
  • Publication Type:
    Conference
  • Authors:
    Kochan M, Modat M, Vercauteren T, White M, Mancini L, Winston GP, McEvoy AW, Thornton JS, Yousry T, Duncan JS, Ourselin S, Stoyanov D
  • Publisher:
    Springer Verlag (Germany)
  • Publication date:
    15/07/2016
  • Published proceedings:
    Lecture Notes in Computer Science
  • Name of conference:
    MICCAI 2016
  • Conference place:
    Athens
  • Conference start date:
    17/10/2016
  • Conference finish date:
    21/10/2016
  • Print ISSN:
    0302-9743
  • Keywords:
    non-rigid registration, similarity measure, neurosurgery
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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