Fast OCT-Based Needle Tracking for Retinal Microsurgery Using Dynamic Spiral Scanning

被引:1
作者
Xu, Pengwei [1 ]
Ourak, Mouloud [1 ]
Borghesan, Gianni [1 ,2 ]
Vander Poorten, Emmanuel [1 ]
机构
[1] Katholieke Univ Leuven, Dept Mech Engn, Leuven 3000, Belgium
[2] Katholieke Univ Leuven, Flanders Make, B-3000 Leuven, Belgium
来源
IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS | 2024年 / 6卷 / 04期
关键词
Needles; Retina; Spirals; Microsurgery; Three-dimensional displays; Tracking; Real-time systems; Real-time instrument tracking; OCT; U-Net segmentation; deep learning; retinal microsurgery; SUBRETINAL INJECTION; SEGMENTATION; ROBOTS; SYSTEM;
D O I
10.1109/TMRB.2024.3464693
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Retinal microsurgery is crucial for treating various ocular diseases, but challenging due to the structure size, physiological tremor and limited depth perception. This study aims to develop an innovative real-time needle tracking system that utilizes only a small amount of Optical Coherence Tomography (OCT) A-scans. We introduce a spiral scanning pattern, that is dynamically updated to efficiently capture the needle tip and the retina area with 2000 A-scans. An imaging pipeline is proposed that initiates with an initial Region of Interest (ROI) identification, followed by image segmentation, 3D reconstruction, and needle pose estimation. The ROI is dynamically adjusted to keep the needle tip centrally within the spiral scan, facilitating tracking at clinically relevant speeds. Preliminary testing on phantom eye models demonstrated that our system can maintain an average tracking error of 0.04 mm in spatial coordinates and an error of 0.06 mm in estimating the distance between the needle tip and the retina. These results suggest the system's potential to enhance surgical outcomes by providing surgeons with improved depth perception and precise, real-time feedback. By efficiently utilizing spirally sampled OCT data, this system sets the groundwork for future integrations of real-time 4D imaging and physiological motion detection capabilities.
引用
收藏
页码:1502 / 1511
页数:10
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