Sa25-01 - AI in diabetic retinopathy screening

Referent/in: Sobha Sivaprasad, London, United Kingdom

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. 

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.

Sa25-04 - Cross-modal self-supervised retinal thickness prediction

Referent/in: Olle Holmberg, München

Sa25-05 - Promising deep learning approaches in OCT imaging

Referent/in: Maximilian Treder, Münster