Persistent and automatic intraoperative 3D digitization of surfaces under dynamic magnifications of an operating microscope

Abstract

One of the major challenges impeding advancement in image-guided surgical (IGS) systems is the soft-tissue deformation during surgical procedures. These deformations reduce the utility of the patient’s preoperative images and may produce inaccuracies in the application of preoperative surgical plans. Solutions to compensate for the tissue deformations include the acquisition of intraoperative tomographic images of the whole organ for direct displacement measurement and techniques that combines intraoperative organ surface measurements with computational biomechanical models to predict subsurface displacements. The later solution has the advantage of being less expensive and amenable to surgical workflow. Several modalities such as textured laser scanners, conoscopic holography, and stereo-pair cameras have been proposed for the intraoperative 3D estimation of organ surfaces to drive patient-specific biomechanical models for the intraoperative update of preoperative images. Though each modality has its respective advantages and disadvantages, stereo-pair camera approaches used within a standard operating microscope is the focus of this article. A new method that permits the automatic and near real-time estimation of 3D surfaces (at 1Hz) under varying magnifications of the operating microscope is proposed. This method has been evaluated on a CAD phantom object and on full-length neurosurgery video sequences (~1 hour) acquired intraoperatively by the proposed stereovision system. To the best of our knowledge, this type of validation study on full-length brain tumor surgery videos has not been done before. The method for estimating the unknown magnification factor of the operating microscope achieves accuracy within 0.02 of the theoretical value on a CAD phantom and within 0.06 on 4 clinical videos of the entire brain tumor surgery. When compared to a laser range scanner, the proposed method for reconstructing 3D surfaces intraoperatively achieves root mean square errors (surface-to-surface distance) in the 0.28-0.81mm range on the phantom object and in the 0.54-1.35mm range on 4 clinical cases. The digitization accuracy of the presented stereovision methods indicate that the operating microscope can be used to deliver the persistent intraoperative input required by computational biomechanical models to update the patient’s preoperative images and facilitate active surgical guidance.

SIFT-FANN: An efficient framework for spatio-spectral fusion of satellite images

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“…FANN library, with its automatic tuning feature provides a faster and simpler way to choose the optimal solution for a particular data. FANN library has been used in many applications (Thomas et al 2011;Kumar et al 2015) to speed up the matching process. As per the authors' knowledge, FANN is not explored for registering satellite images in image fusion application.…”

Neurosurgery and brain shift: review of the state of the art and main contributions of robotics

“…Robotic neurosurgery is undergoing deep changes in recent times, mainly resulting from advances in medical imaging techniques (CT, MRI, f-MRI or DTI) enabling better planning the surgical operation to be performed, [3] and [4]. However, during the medical procedure, the brain shifts and deforms (a phenomenon known as brain shift) because of several factors: loss of cerebrospinal fluid (CSF), the action of gravity, the size and location of the surgical target, resections and drug administration, among others [5]- [7]. Consequently, the spatial relationships and planning of the neurosurgery with preoperative images are altered.…”

A novel craniotomy simulation system for evaluation of stereo-pair reconstruction fidelity and tracking

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