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Open AccessArticle

Towards Optical Imaging for Spine Tracking without Markers in Navigated Spine Surgery

1
Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
2
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm SE-171 46, Sweden & Department of Neurosurgery, Karolinska University Hospital, SE-171 46 Stockholm, Sweden
3
Philips Healthcare, 5684 PC Best, The Netherlands
4
Philips Research, High Tech Campus 36, 5656 AE Eindhoven, The Netherlands
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(13), 3641; https://doi.org/10.3390/s20133641
Received: 19 May 2020 / Revised: 13 June 2020 / Accepted: 22 June 2020 / Published: 29 June 2020
(This article belongs to the Special Issue Sensors for Biomedical Imaging)
Surgical navigation systems are increasingly used for complex spine procedures to avoid neurovascular injuries and minimize the risk for reoperations. Accurate patient tracking is one of the prerequisites for optimal motion compensation and navigation. Most current optical tracking systems use dynamic reference frames (DRFs) attached to the spine, for patient movement tracking. However, the spine itself is subject to intrinsic movements which can impact the accuracy of the navigation system. In this study, we aimed to detect the actual patient spine features in different image views captured by optical cameras, in an augmented reality surgical navigation (ARSN) system. Using optical images from open spinal surgery cases, acquired by two gray-scale cameras, spinal landmarks were identified and matched in different camera views. A computer vision framework was created for preprocessing of the spine images, detecting and matching local invariant image regions. We compared four feature detection algorithms, Speeded Up Robust Feature (SURF), Maximal Stable Extremal Region (MSER), Features from Accelerated Segment Test (FAST), and Oriented FAST and Rotated BRIEF (ORB) to elucidate the best approach. The framework was validated in 23 patients and the 3D triangulation error of the matched features was < 0.5 mm. Thus, the findings indicate that spine feature detection can be used for accurate tracking in navigated surgery. View Full-Text
Keywords: optical sensing; spinal surgery; image processing; image analysis for markerless tracking; patient tracking; image-guided surgery optical sensing; spinal surgery; image processing; image analysis for markerless tracking; patient tracking; image-guided surgery
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Manni, F.; Elmi-Terander, A.; Burström, G.; Persson, O.; Edström, E.; Holthuizen, R.; Shan, C.; Zinger, S.; van der Sommen, F.; de With, P.H.N. Towards Optical Imaging for Spine Tracking without Markers in Navigated Spine Surgery. Sensors 2020, 20, 3641.

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