Registering stereovision surface with preoperative magnetic resonance images for brain shift compensation

Xiaoyao Fan; Songbai Ji; Alex Hartov; David Roberts; Keith Paulsen

doi:10.1117/12.911081

17 February 2012 Registering stereovision surface with preoperative magnetic resonance images for brain shift compensation

Xiaoyao Fan, Songbai Ji, Alex Hartov, David Roberts, Keith Paulsen

Author Affiliations +

Proceedings Volume 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling; 83161C (2012) https://doi.org/10.1117/12.911081
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Intraoperative brain deformation can significantly degrade the accuracy of image guidance using preoperative MR images (pMR). To compensate for brain deformation, biomechanical models have been used to assimilate intraoperative displacement data, compute whole-brain deformation field, and to produce updated MR images (uMR). Stereovision (SV) is an important technique to capture both geometry and texture information of exposed cortical surface at the craniotomy, from which surface displacement data (known as sparse data) can be extracted by registering with pMR to drive the computational model. Approaches that solely utilize geometrical information (e.g., closest point distance (CPD) and iterative closest point (ICP) method) do not seem to capture surface deformation accurately especially when significant lateral shift occurs. In this study, we have developed a texture intensity-based method to register cortical surface reconstructed from stereovision after dural opening with pMR to extract 3D sparse data. First, a texture map is created from pMR using surface geometry before dural opening. Second, a mutual information (MI)-based registration was performed between the texture map and the corresponding stereo image after dural opening to capture the global lateral shift. A block-matching algorithm was then executed to differentiate local displacements in smaller patches. The global and local displacements were finally combined and transformed in 3D following stereopsis. We demonstrate the application of the proposed method with a clinical patient case, and show that the accuracy of the technique is 1-2 mm in terms of model-data misfit with a computation time <10 min.

Citation Download Citation

Xiaoyao Fan, Songbai Ji, Alex Hartov, David Roberts, and Keith Paulsen "Registering stereovision surface with preoperative magnetic resonance images for brain shift compensation", Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83161C (17 February 2012); https://doi.org/10.1117/12.911081

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