OCT-guided Robotic Subretinal Needle Injections: A Deep Learning-Based Registration Approach

Mach K, Wei S, Kim JW, Martin-Gomez A, Zhang P, Kang JU, Nasseri MA, Gehlbach P, Navab N, Iordachita I (2022)

Publication Type: Conference contribution

Publication year: 2022

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 781-786

Conference Proceedings Title: Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

Event location: Las Vegas, NV, USA

ISBN: 9781665468190

DOI: 10.1109/BIBM55620.2022.9995143

Abstract

Subretinal injection (SI) is an ophthalmic surgical procedure that allows for the direct injection of therapeutic substances into the subretinal space to treat vitreoretinal disorders. Although this treatment has grown in popularity, various factors contribute to its difficulty. These include the retina's fragile, nonregenerative tissue, as well as hand tremor and poor visual depth perception. In this context, the usage of robotic devices may reduce hand tremors and facilitate gradual and controlled SI. For the robot to successfully move to the target area, it needs to understand the spatial relationship between the attached needle and the tissue. The development of optical coherence tomography (OCT) imaging has resulted in a substantial advancement in visualizing retinal structures at micron resolution. This paper introduces a novel foundation for an OCT-guided robotic steering framework that enables a surgeon to plan and select targets within the OCT volume. At the same time, the robot automatically executes the trajectories necessary to achieve the selected targets. Our contribution consists of a novel combination of existing methods, creating an intraoperative OCT-Robot registration pipeline. We combined straightforward affine transformation computations with robot kinematics and a deep neural network-determined tool-tip location in OCT. We evaluate our framework's capability in a cadaveric pig eye open-sky procedure and using an aluminum target board. Targeting the subretinal space of the pig eye produced encouraging results with a mean Euclidean error of 23.8μm.

Involved external institutions

Johns Hopkins University (JHU) US United States (USA) (US) Klinikum rechts der Isar DE Germany (DE) Wilmer Eye Institute US United States (USA) (US)

How to cite

APA:

Mach, K., Wei, S., Kim, J.W., Martin-Gomez, A., Zhang, P., Kang, J.U.,... Iordachita, I. (2022). OCT-guided Robotic Subretinal Needle Injections: A Deep Learning-Based Registration Approach. In Donald Adjeroh, Qi Long, Xinghua Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda M. Mondal, Jin Liu (Eds.), Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 (pp. 781-786). Las Vegas, NV, USA: Institute of Electrical and Electronics Engineers Inc..

MLA:

Mach, Kristina, et al. "OCT-guided Robotic Subretinal Needle Injections: A Deep Learning-Based Registration Approach." Proceedings of the 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Las Vegas, NV, USA Ed. Donald Adjeroh, Qi Long, Xinghua Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda M. Mondal, Jin Liu, Institute of Electrical and Electronics Engineers Inc., 2022. 781-786.

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