AIMC Topic: Retinal Cone Photoreceptor Cells

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Neural network assisted annotation and analysis tool to study in-vivo foveolar cone photoreceptor topography.

Scientific reports
The foveola, the central region of the human retina, plays a crucial role in sharp color vision and is challenging to study due to its unique anatomy and technical limitations in imaging. We present ConeMapper, an open-source MATLAB software that int...

Determinants of Cone and Rod Functions in Geographic Atrophy: AI-Based Structure-Function Correlation.

American journal of ophthalmology
PURPOSE: To investigate the association between retinal microstructure and cone and rod function in geographic atrophy (GA) secondary to age-related macular degeneration (AMD) by using artificial intelligence (AI) algorithms.

Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning.

Scientific reports
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excell...

Ontogenic retinal changes in three ecologically distinct elopomorph fishes (Elopomorpha:Teleostei) correlate with light environment and behavior.

Visual neuroscience
Unlike the mammalian retina, the teleost fish retina undergoes persistent neurogenesis from intrinsic stem cells. In marine teleosts, most cone photoreceptor genesis occurs early in the embryonic and larval stages, and rods are added primarily during...