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Bilateral Weighted Adaptive Local Similarity Measure for Registration in Neurosurgery

  • Martin KochanEmail author
  • 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
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9902)

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.

Keywords

Non-rigid registration Similarity measure Neurosurgery 

Notes

Acknowledgments

This work was part funded by the Wellcome Trust (WT101957, WT106882, 201080/Z/16/Z), the Engineering and Physical Sciences Research Council (EPSRC grants EP/N013220/1, EP/N022750/1, EP/N027078/1, NS/A000027/1) and the National Institute for Health Research University College London Hospitals Biomedical Research Centre (NIHR BRC UCLH/UCL High Impact Initiative). MK is supported by the UCL Doctoral Training Programme in Medical and Biomedical Imaging studentship funded by the EPSRC (EP/K502959/1). MM is supported by the UCL Leonard Wolfson Experimental Neurology Centre (PR/ylr/18575) and received further funding from Alzheimer’s Society (AS-PG-15-025). GPW is supported by MRC Clinician Scientist Fellowship (MR/M00841X/1). DS receives further funding from the EU-Horizon2020 project EndoVESPA (H2020-ICT-2015-688592).

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© Springer International Publishing AG 2016

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Authors and Affiliations

  • Martin Kochan
    • 1
    Email author
  • Marc Modat
    • 1
    • 3
  • Tom Vercauteren
    • 1
  • Mark White
    • 1
    • 2
  • Laura Mancini
    • 2
  • Gavin P. Winston
    • 4
    • 5
  • Andrew W. McEvoy
    • 2
  • John S. Thornton
    • 2
  • Tarek Yousry
    • 2
  • John S. Duncan
    • 4
  • Sébastien Ourselin
    • 1
    • 3
  • Danail Stoyanov
    • 1
  1. 1.Centre for Medical Image ComputingUniversity College LondonLondonUK
  2. 2.National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation TrustLondonUK
  3. 3.Dementia Research Centre, Institute of NeurologyUniversity College LondonLondonUK
  4. 4.Department of Clinical and Experimental Epilepsy, Institute of NeurologyUniversity College LondonLondonUK
  5. 5.Epilepsy Society MRI UnitChalfont St PeterUK

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