Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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H. Roodaki, C. Amat di San Filippo, D. Zapp, A. Eslami, N. Navab
A Surgical Guidance System for Big-Bubble Deep Anterior Lamellar Keratoplasty
Proceedings of the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016 (bib)

Deep Anterior Lamellar Keratoplasty using Big-Bubble technique (BB-DALK) is a delicate and complex surgical procedure with a multitude of benefits over Penetrating Keratoplasty (PKP). Yet the steep learning curve and challenges associated with BB-DALK prevents it from becoming the standard procedure for keratoplasty. Optical Coherence Tomography (OCT) aids surgeons to carry out BB-DALK in a shorter time with a higher success rate but also brings complications of its own such as image occlusion by the instrument, the constant need to reposition and added distraction. This work presents a novel real-time guidance system for BB-DALK which is practically a complete tool for smooth execution of the procedure. The guidance system comprises of modified 3D+t OCT acquisitions, advanced visualization, tracking of corneal layers and providing depth information using Augmented Reality. The system is tested by an ophthalmic surgeon performing BB-DALK on several ex vivo pig eyes. Results from multiple evaluations show a maximum tracking error of 8.8 micrometers.
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