Artificial Vision Through Retinal Implants

 

Motivation

Worldwide, over 43 million people are affected by blindness, and this number is continuously rising. More than 2 million individuals suffer from age-related macular degeneration alone. Retinal implants represent an innovative technology aimed at restoring vision.

In Aachen, we have already developed a prototype called Epiret 3. Since the Argus II was taken off the market, there are currently no commercially available retinal implants. The PRIMA implant by Pixium Vision is currently undergoing clinical trials in France, and approval in the USA is expected. To date, more than 500 retinal implants have been successfully implanted worldwide.

The Graduate School 2610 – InnoRetVision, funded by the German Research Foundation (DFG), is a program dedicated to training PhD candidates in the field of retinal implants. We collectively supervise more than 40 doctoral students from RWTH Aachen University, the University of Duisburg-Essen, and Forschungszentrum Jülich.

Scientific Questions

Currently, retinal implants offer very low resolution. The most commonly used Argus II system has only 60 electrodes, equating to a resolution of 6 × 10 pixels. This is insufficient to render even simple images, such as a “Space Invader” (88 = 11 × 8 pixels). Furthermore, nonlinear effects occur, such as the unintended activation of axons (nerve fibers) instead of somas (cell bodies) in the retina. The perceived image quality is limited by severely reduced contrast, and color perception is currently not possible.

Our research aims to overcome these challenges and significantly improve the functionality of retinal implants. This includes work on semantically relevant downsampling, minimizing nonlinear effects, and developing technologies to enhance contrast and enable color perception.

Theses

External Funding

  • DFG GRK 2610, “Innovative Retinal interfaces for optimized Artificial Vision – InnoRetVision”, Project nr. 424556709

Partner

Contact

M.Sc.
Yuli Wu
 +49 241 80 27974
 yuli.wu@lfb.rwth-aachen.de

M.Sc.
Henning Konermann
 +49 241 80 27862
 Henning.Konermann@lfb.rwth-aachen.de

Publications

2024

Yuli Wu, Do Dinh Tan Nguyen, Henning Konermann, Rüveyda Yilmaz, Peter Walter and Johannes Stegmaier
Visual Fixation-Based Retinal Prosthetic Simulation
In: arXiv preprint arXiv:2410.11688

2024

Yuli Wu, Julian Wittmann, Peter Walter and Johannes Stegmaier
Optimizing Retinal Prosthetic Stimuli with Conditional Invertible Neural Networks
In: arXiv preprint arXiv:2403.04884

2024

Yuli Wu, Weidong He, Dennis Eschweiler, Ningxin Dou, Zixin Fan, Shengli Mi, Peter Walter and Johannes Stegmaier
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation
In: IEEE 21st International Symposium on Biomedical Imaging (ISBI)

2023

Yuli Wu, Laura Koch, Peter Walter and Dorit Merhof
Abstract: Convolutional Neural Network-based Inverse Encoder for Optimization of Retinal Prosthetic Stimulation
In: Artificial Vision – The International Symposium on Visual Prosthetics

2023

Yuli Wu, Ivan Karetic, Johannes Stegmaier, Peter Walter and Dorit Merhof
A Deep Learning-based in silico Framework for Optimization on Retinal Prosthetic Stimulation
In: International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

2022

Yuli Wu, Peter Walter and Dorit Merhof
Multiscale Softmax Cross Entropy for Fovea Localization on Color Fundus Photography
In: Bildverarbeitung fuer die Medizin (BVM)