TY - GEN
T1 - Shadow-Based 3D Pose Estimation of Intraocular Instrument Using only 2D Images
AU - Yang, Junjie
AU - Zhao, Zhihao
AU - Maier, Mathias
AU - Huang, Kai
AU - Navab, Nassir
AU - Ali Nasseri, M.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85202444423&partnerID=8YFLogxK
U2 - 10.1109/ICRA57147.2024.10611011
DO - 10.1109/ICRA57147.2024.10611011
M3 - Conference contribution
AN - SCOPUS:85202444423
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 1323
EP - 1329
BT - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Y2 - 13 May 2024 through 17 May 2024
ER -