Arpita Routray, Chaniya Jaroenkunathum, Sungwook Yang, Robert Maclachlan, Jennifer Adeghate, Marjan Fooladi, Joseph Martel, Cameron N. Riviere
{"title":"用激光瞄准光束估计玻璃体视网膜手术的放大-不变视网膜距离","authors":"Arpita Routray, Chaniya Jaroenkunathum, Sungwook Yang, Robert Maclachlan, Jennifer Adeghate, Marjan Fooladi, Joseph Martel, Cameron N. Riviere","doi":"10.1002/rcs.70113","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Virtual fixtures in robot-assisted retinal surgery require knowledge of the position of the retina with respect to the surgical tool to be effective. Retinal surface estimation is a difficult problem due to the lack of features in the captured microscope imagery and a complex light path. A laser aiming beam attached to the tool can be easily detected in the microscope imagery and provide valuable information about the location of the surface.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We propose using the area of a laser aiming beam attached to the surgical tool to determine the distance of the tool from the retina. This area was modified in accordance with the tool width to ensure independence from microscope magnification. Retinal distance is predicted using a dual Kalman filter that combines distance inferred from this metric with information from an optical tracker that tracks the position of the tool in a global coordinate system. This updates both the state and parameters of the system in parallel and allows us to predict retinal distance even with errors in initial parameters.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The laser metric's independence from microscope magnification is demonstrated by plotting the metric at 3 different magnifications for a number of angles. We also predict the distance of the tool from the retina for various random angles at each magnification with median errors of less than 100 μm. Finally, we predict distance at each magnification during freehand motion and validate our results using a force sensor placed underneath the phantom.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Using the area of laser aiming beam attached to the surgical tool, our method can predict the distance of the surgical tool to the retina with errors that are acceptable for implementing virtual fixtures during robot-assisted retinal surgery. The predicted distance is also independent of microscope magnification and can work when initial parameters are not precisely known. Future work will involve adapting this method to in vivo environments and further reduction in prediction errors.</p>\n </section>\n </div>","PeriodicalId":50311,"journal":{"name":"International Journal of Medical Robotics and Computer Assisted Surgery","volume":"21 5","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rcs.70113","citationCount":"0","resultStr":"{\"title\":\"Magnification-Invariant Retinal Distance Estimation for Vitreoretinal Surgery Using a Laser Aiming Beam\",\"authors\":\"Arpita Routray, Chaniya Jaroenkunathum, Sungwook Yang, Robert Maclachlan, Jennifer Adeghate, Marjan Fooladi, Joseph Martel, Cameron N. Riviere\",\"doi\":\"10.1002/rcs.70113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Virtual fixtures in robot-assisted retinal surgery require knowledge of the position of the retina with respect to the surgical tool to be effective. Retinal surface estimation is a difficult problem due to the lack of features in the captured microscope imagery and a complex light path. A laser aiming beam attached to the tool can be easily detected in the microscope imagery and provide valuable information about the location of the surface.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We propose using the area of a laser aiming beam attached to the surgical tool to determine the distance of the tool from the retina. This area was modified in accordance with the tool width to ensure independence from microscope magnification. Retinal distance is predicted using a dual Kalman filter that combines distance inferred from this metric with information from an optical tracker that tracks the position of the tool in a global coordinate system. This updates both the state and parameters of the system in parallel and allows us to predict retinal distance even with errors in initial parameters.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The laser metric's independence from microscope magnification is demonstrated by plotting the metric at 3 different magnifications for a number of angles. We also predict the distance of the tool from the retina for various random angles at each magnification with median errors of less than 100 μm. Finally, we predict distance at each magnification during freehand motion and validate our results using a force sensor placed underneath the phantom.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Using the area of laser aiming beam attached to the surgical tool, our method can predict the distance of the surgical tool to the retina with errors that are acceptable for implementing virtual fixtures during robot-assisted retinal surgery. The predicted distance is also independent of microscope magnification and can work when initial parameters are not precisely known. 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Magnification-Invariant Retinal Distance Estimation for Vitreoretinal Surgery Using a Laser Aiming Beam
Background
Virtual fixtures in robot-assisted retinal surgery require knowledge of the position of the retina with respect to the surgical tool to be effective. Retinal surface estimation is a difficult problem due to the lack of features in the captured microscope imagery and a complex light path. A laser aiming beam attached to the tool can be easily detected in the microscope imagery and provide valuable information about the location of the surface.
Methods
We propose using the area of a laser aiming beam attached to the surgical tool to determine the distance of the tool from the retina. This area was modified in accordance with the tool width to ensure independence from microscope magnification. Retinal distance is predicted using a dual Kalman filter that combines distance inferred from this metric with information from an optical tracker that tracks the position of the tool in a global coordinate system. This updates both the state and parameters of the system in parallel and allows us to predict retinal distance even with errors in initial parameters.
Results
The laser metric's independence from microscope magnification is demonstrated by plotting the metric at 3 different magnifications for a number of angles. We also predict the distance of the tool from the retina for various random angles at each magnification with median errors of less than 100 μm. Finally, we predict distance at each magnification during freehand motion and validate our results using a force sensor placed underneath the phantom.
Conclusions
Using the area of laser aiming beam attached to the surgical tool, our method can predict the distance of the surgical tool to the retina with errors that are acceptable for implementing virtual fixtures during robot-assisted retinal surgery. The predicted distance is also independent of microscope magnification and can work when initial parameters are not precisely known. Future work will involve adapting this method to in vivo environments and further reduction in prediction errors.
期刊介绍:
The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.