ICRA 2024poster0 citations

Shadow-Based 3D Pose Estimation of Intraocular Instrument Using Only 2D Images

Junjie Yang, Zhihao Zhao, Mathias Maier, Kai Huang, Nassir Navab, M. Ali Nasseri

Abstract

In ophthalmic surgeries, such as vitreoretinal operations, surgeons rely on imaging systems, primarily microscopes, for real-time instrument monitoring and motion planning. However, novice surgeons struggle to extract 3D instrument positions from 2D microscope frames, necessitating extensive trial-and-error experience with the background that additional imaging modalities such as iOCT remain inaccessible in most operating rooms. Targeting intraocular assessment within the current surgical setup, this paper presents an imagebased pose estimation method to obtain real-time instrument tip positions in a standard 12mm-radius spherical eyeball model, which links floating instruments with on-the-retinal objects based on the intraocular shadowing principle. We validate this estimation method in a Unity simulator and verify its depth estimation capability using a specially designed eyeball phantom. Both simulator and phantom experiments demonstrate an average needle-tip estimation error within [1.0, 2.0] mm using only 2D microscope frames.

BibTeX
@inproceedings{icra2024_shadowbased3dpos,
  title = {Shadow-Based 3D Pose Estimation of Intraocular Instrument Using Only 2D Images},
  author = {Junjie Yang and Zhihao Zhao and Mathias Maier and Kai Huang and Nassir Navab and M. Ali Nasseri},
  booktitle = {ICRA 2024},
  year = {2024}
}