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Augmented Reality in Image-Guided Robotic Surgery
Published in Terry M. Peters, Cristian A. Linte, Ziv Yaniv, Jacqueline Williams, Mixed and Augmented Reality in Medicine, 2018
Wen Pei Liu, Russell H. Taylor
Similarly, in ophthalmology, researchers created intraoperative mosaics for view expansion. Expanded mosaic views can be used to guide laser photocoagulation, which is currently the standard treatment for sight-threatening diseases worldwide, namely diabetic retinopathy and retinal vein occlusions. For example, Richa et al. (2014) extended the capabilities of a collaborative robot for eye surgery by creating a panoramic view of the retina. Correspondence was established with feature-rich structures, such as vessel branches among images of the fundus through the microscope. The concept of surface reconstruction can extend the application of mosaic views even further. By using a miniature projector for structured light surface reconstruction, Edgcumbe et al. (2015) reported errors less than 2 mm in phantom-based experiments and feasibility in an in vivo proof-of-concept porcine trial.
Minimally Invasive Surgical Robotics
Published in John G Webster, Minimally Invasive Medical Technology, 2016
Robotics have also been applied to various types of eye surgery. One particular application is the use of robotics for automatic placement of bursts of laser light (laser photocoagulation of the retina). Laser photocoagulation can be used to treat diabetic retinopathy (disorder of the retina due to diabetes) and retinal tears. The retinopathy is treated by denaturing areas of the retina around the periphery. However, as many as 3000 bursts of light may be used per retina for treatment. Retinal tears can be treated by mending the tears with the laser.
Steering light in fiber-optic medical devices: a patent review
Published in Expert Review of Medical Devices, 2022
Merle S. Losch, Famke Kardux, Jenny Dankelman, Benno H. W. Hendriks
Ophthalmology is a discipline in which optimal illumination is crucial to guarantee surgical safety and effectiveness [106]. Therefore, light diffusion has found its way into surgical practice in the last decennia. New designs contribute to the growing diversity of surgical illumination options. A second widespread ophthalmologic application is laser photocoagulation, a surgery frequently carried out to prevent vision loss in patients affected by diabetes [107], retinopathy of prematurity [108], and other ocular indications. Nagpal et al. [109] have shown that multi-spot photocoagulation leads to faster, less painful procedures with less collateral damage than standard laser treatment, while achieving similar retinopathy regression in diabetic patients. New designs to create multi-spot patterns therefore show great potential for application in laser photocoagulation.
Multivariate time-between-events monitoring: An overview and some overlooked underlying complexities
Published in Quality Engineering, 2020
Inez M. Zwetsloot, Tahir Mahmood, William H. Woodall
An example of data that would be consistent with the vector-based scenario was described by Li, Sun, and Song (2012). They considered estimation of the failure time distribution in an application of bivariate failure time data arising from the Diabetic Retinopathy Study (DRS) (Huster, Brookmeyer, and Self 1989) . According to Li, Sun, and Song (2012), “The study was conducted by the National Eye Institute to assess the effect of laser photocoagulation in delaying the onset of severe visual loss such as blindness in the patients with diabetic retinopathy. It consisted of 197 high-risk patients. At the beginning of the study, for each patient, one eye was randomly selected for laser photocoagulation and the other was given no treatment, serving as the control for each patient. The times to blindness in both eyes were recorded in months.” Perhaps unsurprisingly, Li, Sun, and Song (2012) found that the times to blindness in the eyes of a patient were dependent. They also found that the failure time of the treated eye tended to be longer than the failure time for the untreated eye. A similar medical example can be found in a headache relief time study where two treatments were compared and for each patient, the relief time was recorded for each of the two treatments (Lu and Bhattacharyya 1991; Gross and Lam 1981). To obtain bivariate TBE data for these studies, one needs to know when the patient entered the study so that the time to each event can be determined. Note that these are examples of vector-based time-between-events data, but the applications involved designed experiments and were not presented as part of a monitoring application.