Automated Detection and Analysis of Photoreceptors in Retinal Imaging

Type: MA thesis

Status: running

Date: June 10, 2024 - December 10, 2024

Supervisors: Mikhail Kulyabin, Andreas Maier

Photoreceptor analysis is crucial for understanding retinal structure and function. This research focuses on automated detection and analysis of cones in retinal images acquired through confocal and calculated imaging techniques. Initially, Images are analyzed using state-of-the-art segmentation methods to extract detailed information. Then, data from both modalities are integrated to achieve comprehensive identification of all detectable cones. Future work includes exploring the potential to detect rod cells in the retinal images for a more holistic understanding of retinal structure.