Monocular Microscope to CT Registration using Pose Estimation of the Incus for Augmented Reality Cochlear Implant Surgery
<|reference_start|>Monocular Microscope to CT Registration using Pose Estimation of the Incus for Augmented Reality Cochlear Implant Surgery: 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.<|reference_end|>
@article{zhang2024monocular,
    title={Monocular Microscope to CT Registration using Pose Estimation of the
  Incus for Augmented Reality Cochlear Implant Surgery},
    author={Yike Zhang, Eduardo Davalos, Dingjie Su, Ange Lou, Jack H. Noble},
    journal={arXiv preprint arXiv:2403.07219},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.07219},
    primaryClass={cs.CV}
}