EyeLS: Shadow-Guided Instrument Landing System for Intraocular Target
  Approaching in Robotic Eye Surgery
Junjie Yang Zhihao Zhao Siyuan Shen Daniel Zapp Mathias Maier Kai Huang Nassir Navab M. Ali Nasseri
Robotic ophthalmic surgery is an emerging technology to facilitate
high-precision interventions such as retina penetration in subretinal injection
and removal of floating tissues in retinal detachment depending on the input
imaging modalities such as microscopy and intraoperative OCT (iOCT). Although
iOCT is explored to locate the needle tip within its range-limited ROI, it is
still difficult to coordinate iOCT's motion with the needle, especially at the
initial target-approaching stage. Meanwhile, due to 2D perspective projection
and thus the loss of depth information, current image-based methods cannot
effectively estimate the needle tip's trajectory towards both retinal and
floating targets. To address this limitation, we propose to use the shadow
positions of the target and the instrument tip to estimate their relative depth
position and accordingly optimize the instrument tip's insertion trajectory
until the tip approaches targets within iOCT's scanning area. Our method
succeeds target approaching on a retina model, and achieves an average depth
error of 0.0127 mm and 0.3473 mm for floating and retinal targets respectively
in the surgical simulator without damaging the retina.