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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1323-1329
Number of pages7
ISBN (Electronic)9798350384574
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Robotics and Automation, ICRA 2024 - Yokohama, Japan
Duration: 13 May 202417 May 2024

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Country/TerritoryJapan
CityYokohama
Period13/05/2417/05/24

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