Real-Time Integration of Optical Coherence Tomography Thickness Map Overlays for Enhanced Visualization in Epiretinal Membrane Surgery: A Pilot Study

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Publicat a:Bioengineering vol. 12, no. 3 (2025), p. 271
Autor principal: Turgut, Ferhat
Altres autors: Ueda, Keisuke, Saad, Amr, Spitznagel, Tahm, Luca von Felten, Matsumoto, Takashi, Santos, Rui, de Smet, Marc D, Nagy, Zoltán Zsolt, Becker, Matthias D, Somfai, Gábor Márk
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022 |a 2306-5354 
024 7 |a 10.3390/bioengineering12030271  |2 doi 
035 |a 3181355617 
045 2 |b d20250101  |b d20251231 
100 1 |a Turgut, Ferhat  |u Department of Ophthalmology, Stadtspital Zürich, 8063 Zurich, Switzerland; <email>ferhat.turgut@stadtspital.ch</email> (F.T.); <email>tahm.spitznagel@stadtspital.ch</email> (T.S.); ; Spross Research Institute, 8055 Zurich, Switzerland; Gutblick Research, 8088 Pfäffikon, Switzerland; Department of Ophthalmology, Semmelweis University, 1428 Budapest, Hungary 
245 1 |a Real-Time Integration of Optical Coherence Tomography Thickness Map Overlays for Enhanced Visualization in Epiretinal Membrane Surgery: A Pilot Study 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a (1) Background: The process of epiretinal membrane peeling (MP) requires precise intraoperative visualization to achieve optimal surgical outcomes. This study investigates the integration of preoperative Optical Coherence Tomography (OCT) images into real-time surgical video feeds, providing a dynamic overlay that enhances the decision-making process during surgery. (2) Methods: Five MP surgeries were analyzed, where preoperative OCT images were first manually aligned with the initial frame of the surgical video by selecting five pairs of corresponding points. A homography transformation was then computed to overlay the OCT onto that first frame. Subsequently, for consecutive frames, feature point extraction (the Shi–Tomasi method) and optical flow computation (the Lucas–Kanade algorithm) were used to calculate frame-by-frame transformations, which were applied to the OCT image to maintain alignment in near real time. (3) Results: The method achieved a 92.7% success rate in optical flow detection and maintained an average processing speed of 7.56 frames per second (FPS), demonstrating the feasibility of near real-time application. (4) Conclusions: The developed approach facilitates enhanced intraoperative visualization, providing surgeons with easier retinal structure identification which results in more comprehensive data-driven decisions. By improving surgical precision while potentially reducing complications, this technique benefits both surgeons and patients. Furthermore, the integration of OCT overlays holds promise for advancing robot-assisted surgery and surgical training protocols. This pilot study establishes the feasibility of real-time OCT integration in MP and opens avenues for broader applications in vitreoretinal procedures. 
610 4 |a Carl Zeiss Meditec AG 
651 4 |a Switzerland 
651 4 |a United States--US 
651 4 |a Germany 
653 |a Tomography 
653 |a Surgeons 
653 |a Pilot projects 
653 |a Optical flow (image analysis) 
653 |a Retina 
653 |a Medical imaging 
653 |a Surgical outcomes 
653 |a Feasibility studies 
653 |a Visualization 
653 |a Robotic surgery 
653 |a Processing speed 
653 |a Distributed processing 
653 |a Artificial intelligence 
653 |a Frames (data processing) 
653 |a Surgery 
653 |a Time integration 
653 |a Algorithms 
653 |a Membranes 
653 |a Real time 
653 |a Integration 
653 |a Decision making 
653 |a Optical Coherence Tomography 
700 1 |a Ueda, Keisuke  |u Medical Dataway AG, 6300 Zug, Switzerland 
700 1 |a Saad, Amr  |u Department of Ophthalmology, Stadtspital Zürich, 8063 Zurich, Switzerland; <email>ferhat.turgut@stadtspital.ch</email> (F.T.); <email>tahm.spitznagel@stadtspital.ch</email> (T.S.); ; Spross Research Institute, 8055 Zurich, Switzerland 
700 1 |a Spitznagel, Tahm  |u Department of Ophthalmology, Stadtspital Zürich, 8063 Zurich, Switzerland; <email>ferhat.turgut@stadtspital.ch</email> (F.T.); <email>tahm.spitznagel@stadtspital.ch</email> (T.S.); ; Spross Research Institute, 8055 Zurich, Switzerland 
700 1 |a Luca von Felten  |u Medical Dataway AG, 6300 Zug, Switzerland 
700 1 |a Matsumoto, Takashi  |u Medical Dataway AG, 6300 Zug, Switzerland 
700 1 |a Santos, Rui  |u Department of Ophthalmology, Stadtspital Zürich, 8063 Zurich, Switzerland; <email>ferhat.turgut@stadtspital.ch</email> (F.T.); <email>tahm.spitznagel@stadtspital.ch</email> (T.S.); ; Spross Research Institute, 8055 Zurich, Switzerland 
700 1 |a de Smet, Marc D  |u New York Eye and Ear Infirmary of Mt Sinai, Icahn School of Medicine, New York, NY 10029, USA; <email>mddesmet1@mac.com</email>; MIOS sa/Helvetia Retina Associates, 1005 Lausanne, Switzerland; Chargé de Recherche, Université Libre de Bruxelles, 1050 Brussels, Belgium 
700 1 |a Nagy, Zoltán Zsolt  |u Department of Ophthalmology, Semmelweis University, 1428 Budapest, Hungary 
700 1 |a Becker, Matthias D  |u Department of Ophthalmology, Stadtspital Zürich, 8063 Zurich, Switzerland; <email>ferhat.turgut@stadtspital.ch</email> (F.T.); <email>tahm.spitznagel@stadtspital.ch</email> (T.S.); ; Spross Research Institute, 8055 Zurich, Switzerland; Department of Ophthalmology, University of Heidelberg, 69117 Heidelberg, Germany 
700 1 |a Somfai, Gábor Márk  |u Department of Ophthalmology, Stadtspital Zürich, 8063 Zurich, Switzerland; <email>ferhat.turgut@stadtspital.ch</email> (F.T.); <email>tahm.spitznagel@stadtspital.ch</email> (T.S.); ; Spross Research Institute, 8055 Zurich, Switzerland; Department of Ophthalmology, Semmelweis University, 1428 Budapest, Hungary 
773 0 |t Bioengineering  |g vol. 12, no. 3 (2025), p. 271 
786 0 |d ProQuest  |t Engineering Database 
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