Deep Learning in Ophthalmology - where are we heading?

Symposium im Rahmen der DOG 2021 online
Online, Deutschland
Veranstaltungsnummer: 37006
Zertifizierung: beantragt
Gebühren ab: gebührenfrei
verfügbare Plätze: unbegrenzt
Sprache: Englisch

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  • Datum
    30.09.2021, 15:00 - 15:45
    DOG - Deutsche Ophthalmologische Gesellschaft e.V.
    Automated image analysis has become an indispensable tool in ophthalmology. Algorithms are already being used in studies and will soon be incorporated into our clinical routine, supporting medical decision-making. This international symposium will provide an overview on recent developments and their clinical applicability of deep learning in ophthalmology.


    Teilnehmer max.

    Gebühren ab
  • Vorsitzende/r: S. Sivaprasad, London, United Kingdom
    Vorsitzende/r: K. Kortüm, Ulm
    Organisator / Vorsitzender: M. Wintergerst, Bonn
    15:00 – 15:09
    Do05-01 - Deep Learning for Diabetes Screening in Singapore
    Referent/in: Gavin Tan, Singapur, Singapore
    15:09 – 15:18 
    Do05-02 - Artificial Intelligence Approaches to Understand Functional Vision Defects
    Referent/in: Tobias Elze, Boston, United States

    While machine learning approaches have become popular in recent years to investigate ophthalmic imaging of retinal structure, their utility to better understand visual function seems less obvious. Here, we introduce recent developments of artificial intelligence to improve the diagnosis of functional vision loss, to monitor its progression over time, and to relate retinal structure to specific visual impairments. Particularly for the disease of glaucoma, we demonstrate how machine learning made it possible to define and quantify functional disease subtypes and to identify subtype specific retinal biomarkers.

    15:18 – 15:27 
    Do05-03 - Beyond Retinal Layers: AI-based Endpoints for Non-Exudative Age-Related Macular Degeneration
    Referent/in: Maximilian Pfau, Bonn
    15:27 – 15:36
    Do05-04 - Longitudinal Analysis of nAMD anti-VEGF Treatment Using Deep Learning
    Referent/in: Olle Holmberg, München

    We perform longitudinal analysis of nAMD anti-VEGF Treatment Using Deep Learning. Specifically, we use Deep learning for semantic segmentation to investigate the influence of multiple clinical features in the retina on the treatment outcomes of patients with nAMD.

    15:36 – 15:45
    Do05-05 - Deep Learning for Detection of Peripheral Arterial Disease on Retinal Images
    Referent/in: Simon Müller, Bonn

    Using modern convolutional neural networks it is possible to detect systemic diseases - like peripheral artery disease. Furthermore our approach makes it possible to inspect the decision making process of the model using a novel attention mechanism. In this talk I will present the technical details of our approach, how well it performed and how it can improve diagnostics in ophthalmology.

  • Die Veranstaltung findet Online statt. Channel 1


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