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Deformable MRI-Ultrasound Registration via Attribute Matching and Mutual-Saliency Weighting for Image-Guided Neurosurgery

  • Inês Machado
  • Matthew Toews
  • Jie Luo
  • Prashin Unadkat
  • Walid Essayed
  • Elizabeth George
  • Pedro Teodoro
  • Herculano Carvalho
  • Jorge Martins
  • Polina Golland
  • Steve Pieper
  • Sarah Frisken
  • Alexandra Golby
  • William Wells III
  • Yangming Ou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11042)

Abstract

Intraoperative brain deformation reduces the effectiveness of using preoperative images for intraoperative surgical guidance. We propose an algorithm for deformable registration of intraoperative ultrasound (US) and preoperative magnetic resonance (MR) images in the context of brain tumor resection. From each image voxel, a set of multi-scale and multi-orientation Gabor attributes is extracted from which optimal components are selected to establish a distinctive morphological signature of the anatomical and geometric context of its surroundings. To match the attributes across image pairs, we assign higher weights – higher mutual-saliency values - to those voxels more likely to establish reliable correspondences across images. The correlation coefficient is used as the similarity measure to evaluate effectiveness of the algorithm for multi-modal registration. Free-form deformation and discrete optimization are chosen as the deformation model and optimization strategy, respectively. Experiments demonstrate our methodology on registering preoperative T2-FLAIR MR to intraoperative US in 22 clinical cases. Using manually labelled corresponding landmarks between preoperative MR and intraoperative US images, we show that the mean target registration error decreases from an initial value of 5.37 ± 4.27 mm to 3.35 ± 1.19 mm after registration.

Keywords

Brain shift Intraoperative ultrasound Image registration Attribute matching Gabor filter bank Mutual-saliency 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Inês Machado
    • 1
    • 2
  • Matthew Toews
    • 3
  • Jie Luo
    • 1
    • 4
  • Prashin Unadkat
    • 5
  • Walid Essayed
    • 5
  • Elizabeth George
    • 1
  • Pedro Teodoro
    • 2
  • Herculano Carvalho
    • 6
  • Jorge Martins
    • 2
  • Polina Golland
    • 7
  • Steve Pieper
    • 1
    • 8
  • Sarah Frisken
    • 1
  • Alexandra Golby
    • 5
  • William Wells III
    • 1
    • 7
  • Yangming Ou
    • 9
  1. 1.Department of RadiologyBrigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  2. 2.Instituto Superior Técnico, Universidade de LisboaLisbonPortugal
  3. 3.École de Technologie SupérieureMontrealCanada
  4. 4.Graduate School of Frontier SciencesUniversity of TokyoTokyoJapan
  5. 5.Department of NeurosurgeryBrigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  6. 6.Department of NeurosurgeryHospital de Santa Maria, CHLNLisbonPortugal
  7. 7.Computer Science and Artificial Intelligence LaboratoryMITCambridgeUSA
  8. 8.Isomics, Inc.CambridgeUSA
  9. 9.Department of Pediatrics and RadiologyBoston Children’s Hospital, Harvard Medical SchoolBostonUSA

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