Multimodal imaging and evaluation in the age of artificial intelligence

Abstract

Multimodal imaging is able to image the retina in unprecedented detail, and the joint analysis (integration) of these data not only enables the securing of diagnoses, but also a more precise definition; however, humans encounter temporal and cognitive limitations in the analysis of this amount of information, so that the potential of a joint examination of the findings is largely unused to date. Automatic image processing and methods, which are summarized under the collective term of artificial intelligence (AI), are able to overcome the bottleneck in the evaluation and to exploit the full potential of the available data. A basic understanding of AI methods and the ability to implement them will become increasingly more important for ophthalmologists in the future. In this article we give an insight into the functionality of AI methods and the current state of research in the field of automatic image analysis.

Publication
In Der Ophthalmologe
Olivier Morelle
Olivier Morelle
Data Scientist - Medical Imaging

My research interest is on the development and application of machine learning methods on ophthalmological data.