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OCTlab – University of Basel Applied Research in Optical Coherence Tomography, Artificial Intelligence and Robotics

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Welcome to the OCTLab, the OCT research group for OCT technology, Virtual Ophthalmology, Artificial Intelligence (AI) and Robotics of the Department of Ophthalmology at the University of Basel. Optical coherence tomography (OCT) is a new, non-invasive imaging technology that uses laser waves to detect pathologies in diseases as age related macular degeneration (AMD), glaucoma, diabetes, multiple sclerosis (MS), tumors of the eye or brain. The OCTlab does applied research and Quality Assurance Studies in the field of optical coherence tomography and targets to save human vision. The University of Basel was founded in 1460 and is the oldest University in Switzerland.


ForAuthors TVST

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Acknowledgments e. References f. Figure legends, tables, and figures, if not embedded in text Lines and pages should be numbered. The title page, which must be part of the main manuscript file, should include the title, authors' full names and institutions, and other manuscript information such as word count and grant information. The title must contain no more than 150 characters, including punctuation and spaces. A structured abstract of fewer than 250 words is required for articles and should be arranged under the following headings: Purpose, Methods, Results, Conclusions, Translational Relevance (a one-sentence description of how your work bridges the gap between basic research and clinical care). Define abbreviations at first mention, and do not include references.


Chinese Hospital in Guangdong deploys AI cameras to detect blindness-causing diseases

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Last week, Deqing county hospital in Guangdong Province launched free consultations featuring artificial-intelligence (AI) cameras to detect ocular fundus diseases, which are major causes of blindness, according to a report by Xinhua News. About 300 residents from Zhaoqing City in Dequing County attended the free consultation sessions. The hospital became the first to use the device, co-developed by China's search engine Baidu and Sun Yat-sen University, to serve the general public. The instrument is capable of diagnosing three types of fundus disorders -- diabetic retinopathy, glaucoma and macular degeneration. It scans the eyes and generates a report in 10 seconds, all done without the need for an ophthalmologist to be present.


Artificial intelligence and deep learning in ophthalmology

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Funding This project received funding from the National Medical Research Council (NMRC), Ministry of Health (MOH), Singapore National Health Innovation Center, Innovation to Develop Grant (NHIC-I2D-1409022), SingHealth Foundation Research Grant (SHF/FG648S/2015), and the Tanoto Foundation, and unrestricted donations to the Retina Division, Johns Hopkins University School of Medicine. PAK is supported by a UK National Institute for Health Research (NIHR) Clinician Scientist Award (NIHR-CS--2014-12-023). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.