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Yang X, Clements LW, Luo M, et al. Stereovision-based integrated system for point cloud reconstruction and simulated brain shift validation. J Med Imaging (Bellingham). 2017;4(3):035002doi: 10.1117/1.JMI.4.3.035002.
Yang, X., Clements, L. W., Luo, M., Narasimhan, S., Thompson, R. C., Dawant, B. M., & Miga, M. I. (2017). Stereovision-based integrated system for point cloud reconstruction and simulated brain shift validation. Journal of medical imaging (Bellingham, Wash.), 4(3), 035002. https://doi.org/10.1117/1.JMI.4.3.035002
Yang, Xiaochen, et al. "Stereovision-based integrated system for point cloud reconstruction and simulated brain shift validation." Journal of medical imaging (Bellingham, Wash.) vol. 4,3 (2017): 035002. doi: https://doi.org/10.1117/1.JMI.4.3.035002
Yang X, Clements LW, Luo M, Narasimhan S, Thompson RC, Dawant BM, Miga MI. Stereovision-based integrated system for point cloud reconstruction and simulated brain shift validation. J Med Imaging (Bellingham). 2017 Jul;4(3):035002. doi: 10.1117/1.JMI.4.3.035002. Epub 2017 Sep 12. PMID: 28924572; PMCID: PMC5594359.
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J Med Imaging (Bellingham). 2017 Jul;4(3):035002. doi: 10.1117/1.JMI.4.3.035002. Epub 2017 Sep 12.

Stereovision-based integrated system for point cloud reconstruction and simulated brain shift validation.

Journal of medical imaging (Bellingham, Wash.)

Xiaochen Yang, Logan W Clements, Ma Luo, Saramati Narasimhan, Reid C Thompson, Benoit M Dawant, Michael I Miga

Affiliations

  1. Vanderbilt University, Department of Electrical Engineering and Computer Science, Nashville, Tennessee, United States.
  2. Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.
  3. Vanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States.
  4. Vanderbilt University Medical Center, Department of Radiology, Nashville, Tennessee, United States.

PMID: 28924572 PMCID: PMC5594359 DOI: 10.1117/1.JMI.4.3.035002

Abstract

Intraoperative soft tissue deformation, referred to as brain shift, compromises the application of current image-guided surgery navigation systems in neurosurgery. A computational model driven by sparse data has been proposed as a cost-effective method to compensate for cortical surface and volumetric displacements. We present a mock environment developed to acquire stereoimages from a tracked operating microscope and to reconstruct three-dimensional point clouds from these images. A reconstruction error of 1 mm is estimated by using a phantom with a known geometry and independently measured deformation extent. The microscope is tracked via an attached tracking rigid body that facilitates the recording of the position of the microscope via a commercial optical tracking system as it moves during the procedure. Point clouds, reconstructed under different microscope positions, are registered into the same space to compute the feature displacements. Using our mock craniotomy device, realistic cortical deformations are generated. When comparing our tracked microscope stereo-pair measure of mock vessel displacements to that of the measurement determined by the independent optically tracked stylus marking, the displacement error was [Formula: see text] on average. These results demonstrate the practicality of using tracked stereoscopic microscope as an alternative to laser range scanners to collect sufficient intraoperative information for brain shift correction.

Keywords: accuracy; brain shift; intraoperative imaging; reconstruction; stereopsis; stereoscopic microscope; tracking

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