# Fast 5DOF Needle Tracking in iOCT

arXiv: https://arxiv.org/abs/1802.06446 · HTML: https://mlsanity.com/paper/1802.06446/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Feb 2018.

## Built on by (most cited first, 3 of 3)

- [Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing](https://mlsanity.com/paper/2301.07204/) (2023)
- [Unsupervised out-of-distribution detection for safer robotically guided retinal microsurgery](https://mlsanity.com/paper/2304.05040/) (2023)
- [EyeLS: Shadow-Guided Instrument Landing System for Intraocular Target Approaching in Robotic Eye Surgery](https://mlsanity.com/paper/2311.08799/) (2023)

## Abstract (arXiv)

Purpose. Intraoperative Optical Coherence Tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable direct analysis of instrument-tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method. The intersection of the needle with the iOCT scan is detected by a peculiar multi-step ellipse fitting that takes advantage of the directionality of the modality. The geometric modelling allows us to use the ellipse parameters and provide them into a latency aware estimator to infer the 5DOF pose during needle movement. Results. Experiments on phantom data and ex-vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion. Using solely crosssectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.5 ms on a CPU.