Home /Research /Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing
LEARNING

Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing

Shervin Dehghani, Michael Sommersperger, Peiyao Zhang, Alejandro Martin‐Gomez, Benjamin Busam, Peter Gehlbach, Nassir Navab, M. Ali Nasseri, Iulian Iordachita

Year
2023
Citations
5

Abstract

, a volume slicing approach for rapid instrument pose estimation, which is enabled by Convolutional Neural Networks (CNNs). Our experiments on ex-vivo porcine eyes demonstrate the precision and repeatability of the method. Finally, we discuss identified challenges in this work and suggest potential solutions to further the development of such systems.

Keywords

Computer scienceArtificial intelligenceRoboticsConvolutional neural networkSlicingComputer visionRobotReal-time computingHuman–computer interactionComputer graphics (images)

Related papers

Browse all LEARNING papers