Sa25 Deep Learning - recent developments in Ophthalmology
Symposium of the DOG 2020 Online
Sa25 Deep Learning - recent developments in Ophthalmology
Symposium of the DOG 2020 Online
INTERPLAN AG
Congress, Meeting & Event Management AG
Landsberger Straße 155
DE - 80687 München
Tel.: +49 (0)89 548 234 35
Tel.: +49 (0)89 548 234 0
Fax: +49 (0)89 548 234 43
Fax: +49 (0)89 548 234 44
Chairman
Sobha Sivaprasad, London, United Kingdom
Karsten Kortüm, München
Maximilian Wintergerst, Bonn
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Basisinformation
Datum10.10.2020, 17:30 - 18:15SpracheEnglischGebühren abgebührenfreiVeranstalterDOG - Deutsche Ophthalmologische Gesellschaft e.V.
OrganisatorINTERPLAN AG
Congress, Meeting & Event Management AG
Landsberger Straße 155
DE - 80687 München
Tel.: +49 (0)89 548 234 35
Tel.: +49 (0)89 548 234 0
Fax: +49 (0)89 548 234 43
Fax: +49 (0)89 548 234 44Chairman
Sobha Sivaprasad, London, United Kingdom
Karsten Kortüm, München
Maximilian Wintergerst, Bonn
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Programm
17:30 – 17:39
Sa25-01 - AI in diabetic retinopathy screening
Referent/in: Sobha Sivaprasad, London, United Kingdom
17:39 – 17:48 Sa25-02 - Beyond traditional applications of AI to ophthalmology: everything the human eye cannot see
Referent/in: Carlos Ciller, Bern, Switzerland
Today Artificial Intelligence in the form of Machine Learning is gradually being integrated in tools to support ophthalmologists with tasks such as identification, localization and quantification of pathological biomarkers linked to the development of eye diseases. However, there are many more ways in which machine learning can support the eye care professional. This presentation will cover some of these contributions that the eye simply cannot see.
17:48 – 17:57 Sa25-03 - Deep Learning for the analysis of outer retinal layers on OCT
Referent/in: Olivier Morelle, Bonn
Reliable quantification of ophthalmological imaging data is essential for large epidemiological studies and an important stepstone towards personalized treatment of retinal diseases. This presentation will focus on the analysis of the outer retinal layers with a deep learning approach.
17:57 – 18:06 Sa25-04 - Cross-modal self-supervised retinal thickness prediction
Referent/in: Olle Holmberg, München
18:06 – 18:15 Sa25-05 - Promising deep learning approaches in OCT imaging
Referent/in: Maximilian Treder, Münster
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