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Non-rigid Deformation Pipeline for Compensation of Superficial Brain Shift

  • Filipe M. M. Marreiros
  • Sandro Rossitti
  • Chunliang Wang
  • Örjan Smedby
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)

Abstract

The correct visualization of anatomical structures is a critical component of neurosurgical navigation systems, to guide the surgeon to the areas of interest as well as to avoid brain damage. A major challenge for neuronavigation systems is the brain shift, or deformation of the exposed brain in comparison to preoperative Magnetic Resonance (MR) image sets. In this work paper, a non-rigid deformation pipeline is proposed for brain shift compensation of preoperative imaging datasets using superficial blood vessels as landmarks. The input was preoperative and intraoperative 3D image sets of superficial vessel centerlines. The intraoperative vessels (obtained using 3 Near-Infrared cameras) were registered and aligned with preoperative Magnetic Resonance Angiography vessel centerlines using manual interaction for the rigid transformation and, for the non-rigid transformation, the non-rigid point set registration method Coherent Point Drift. The rigid registration transforms the intraoperative points from the camera coordinate system to the preoperative MR coordinate system, and the non-rigid registration deals with local transformations in the MR coordinate system. Finally, the generation of a new deformed volume is achieved with the Thin-Plate Spline (TPS) method using as control points the matches in the MR coordinate system found in the previous step. The method was tested in a rabbit brain exposed via craniotomy, where deformations were produced by a balloon inserted into the brain. There was a good correlation between the real state of the brain and the deformed volume obtained using the pipeline. Maximum displacements were approximately 4.0 mm for the exposed brain alone, and 6.7 mm after balloon inflation.

Keywords

Rigid Registration Rabbit Brain Brain Shift Preoperative Magnetic Resonance Neuronavigation System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Filipe M. M. Marreiros
    • 1
  • Sandro Rossitti
    • 2
  • Chunliang Wang
    • 3
  • Örjan Smedby
    • 4
  1. 1.Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
  2. 2.Department of Science and Technology (ITN) - Media and Information Technology (MIT)Linköping UniversityLinköpingSweden
  3. 3.Department of Radiology (IMH)Linköping UniversityLinköpingSweden
  4. 4.Department of Neurosurgery, County Council of ÖstergötlandLinköping UniversityLinköpingSweden

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