Low-latency system for evaluation of image-enhancement-algorithms on patients using subretinal implants

Area of Science:

• Biomedical Engineering
• Computer Vision
• Ophthalmology

Background:

• Hereditary retinal degeneration diseases cause vision loss.
• Subretinal implants offer partial vision restoration.
• Image processing can enhance implant-mediated vision.

Purpose of the Study:

• To develop a flexible, real-time system for testing image enhancement algorithms for subretinal implant users.
• To improve the visual perception of patients with retinal implants.

Main Methods:

• A real-time system was created, including a camera, computational unit, and head-mounted display.
• The system captures and displays real-world scenes with low latency and true-to-scale representation.
• Pixel-based image enhancement algorithms were applied to the captured visual data.

Main Results:

• The system successfully records and displays reality on a head-mounted display with minimal delay.
• It allows for the application and testing of various image enhancement algorithms.
• The system provides a flexible platform for modifying perceived images for subretinal implant patients.

Conclusions:

• The developed real-time system offers a flexible software solution for enhancing visual perception in patients with subretinal implants.
• This approach can significantly improve the effectiveness of current retinal implant technology.
• Further research can explore advanced image processing techniques to optimize visual restoration.