Abstract
PURPOSE: Intraoperative optical coherence tomography (iOCT) was recently introduced as a new modality for ophthalmic surgeries. It provides real-time cross-sectional information at a very high resolution. However, properly positioning the scan location during surgery is cumbersome and time-consuming, as a surgeon needs both his hands for surgery. The goal of the present study is to present a method to automatically position an iOCT scan on an anatomy of interest in the context of anterior segment surgeries. METHODS: First, a voice recognition algorithm using a context-free grammar is used to obtain the desired pose from the surgeon. Then, the limbus circle is detected in the microscope image and the iOCT scan is placed accordingly in the X-Y plane. Next, an iOCT sweep in Z direction is conducted and the scan is placed to centre the topmost structure. Finally, the position is fine-tuned using semantic segmentation and a rule-based system. RESULTS: The logic to position the scan location on various anatomies was evaluated on ex vivo porcine eyes (10 eyes for corneal apex and 7 eyes for cornea, sclera and iris). The mean euclidean distances (± standard deviation) was 76.7 (± 59.2) pixels and 0.298 (± 0.229) mm. The mean execution time (± standard deviation) in seconds for the four anatomies was 15 (± 1.2). The scans have a size of 1024 by 1024 pixels. The method was implemented on a Carl Zeiss OPMI LUMERA 700 with RESCAN 700. CONCLUSION: The present study introduces a method to fully automatically position an iOCT scanner. Providing the possibility of changing the OCT scan location via voice commands removes the burden of manual device manipulation from surgeons. This in turn allows them to keep their focus on the surgical task at hand and therefore increase the acceptance of iOCT in the operating room.