Monocular Microscope to CT Registration using Pose Estimation of the Incus for Augmented Reality Cochlear Implant Surgery (2403.07219v1)
Abstract: For those experiencing severe-to-profound sensorineural hearing loss, the cochlear implant (CI) is the preferred treatment. Augmented reality (AR) aided surgery can potentially improve CI procedures and hearing outcomes. Typically, AR solutions for image-guided surgery rely on optical tracking systems to register pre-operative planning information to the display so that hidden anatomy or other important information can be overlayed and co-registered with the view of the surgical scene. In this paper, our goal is to develop a method that permits direct 2D-to-3D registration of the microscope video to the pre-operative Computed Tomography (CT) scan without the need for external tracking equipment. Our proposed solution involves using surface mapping of a portion of the incus in surgical recordings and determining the pose of this structure relative to the surgical microscope by performing pose estimation via the perspective-n-point (PnP) algorithm. This registration can then be applied to pre-operative segmentations of other anatomy-of-interest, as well as the planned electrode insertion trajectory to co-register this information for the AR display. Our results demonstrate the accuracy with an average rotation error of less than 25 degrees and a translation error of less than 2 mm, 3 mm, and 0.55% for the x, y, and z axes, respectively. Our proposed method has the potential to be applicable and generalized to other surgical procedures while only needing a monocular microscope during intra-operation.
- Holden, L. K., Finley, C. C., Firszt, J. B., Holden, T. A., Brenner, C., Potts, L. G., Gotter, B. D., Vanderhoof, S. S., Mispagel, K., Heydebrand, G., and Skinner, M. W., “Factors affecting open-set word recognition in adults with cochlear implants,” Ear Hear 34, 342–360 (May-Jun 2013).
- Labadie, R. and Noble, J., “Preliminary results with image-guided cochlear implant insertion techniques,” Otol Neurotol 39, 922–928 (Aug 2018).
- Vávra, P., Roman, J., Zonča, P., Ihnát, P., Němec, M., Kumar, J., Habib, N., and El-Gendi, A., “Recent development of augmented reality in surgery: A review,” J Healthc Eng 2017, 4574172 (2017). Epub 2017 Aug 21.
- Zakharov, S., Shugurov, I., and Ilic, S., “DPOD: dense 6d pose object detector in RGB images,” CoRR abs/1902.11020 (2019).
- Wang, H., Sridhar, S., Huang, J., Valentin, J., Song, S., and Guibas, L. J., “Normalized object coordinate space for category-level 6d object pose and size estimation,” CoRR abs/1901.02970 (2019).
- Zhang, Y. and Noble, J. H., “Self-supervised registration and segmentation on ossicles with a single ground truth label,” in [Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling ], 12466, 222–227, SPIE (2023).
- Jocher, G., Chaurasia, A., and Qiu, J., “YOLO by Ultralytics,” https://github.com/ultralytics/ultralytics (2023).
- Zhang, Y., “Vision6D,” https://github.com/ykzzyk/vision6D (2023).