Automated Detection and Analysis of Photoreceptors in Retinal Imaging

📋 Type MA thesis
Status finished
📅 Duration Jun 10, 2024 – Dec 10, 2024
👤 Primary supervisors Mikhail Kulyabin Andreas Maier
🎓 Student Prajol Shrestha Information and Communication Technology

Abstract:
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.