• Automatically counts ganglion cells from fluorescent fundus images.

• Identifies blood vessels and filters out non-ganglion cell targets surrounding them.

• Removes irrelevant targets, such as fluorescent bright spots, to ensure accurate counting.

• Computes quantitative indicators:

Total number of ganglion cells.

Ganglion cell density.

Average cell size.

Total area and average intensity of fluorescent spots.

• Supports images from multiple animal categories and magnifications (4x, 10x, 20x, 40x).

• Precisely detects red pigment locations within fundus images.

• Excludes overexposed reflective areas to maintain calculation accuracy.

• Calculates comprehensive quantitative indicators, including:

     Total area of red pigment pixels.

     Red pigment saturation.

     Average, maximum, minimum, and median intensity of red pigment.

•Identifies regions of sparse blood vessels with low folding in retinal images.

•Detects and locates intravascular cells within the region of interest.

•Classifies cells into pericytes and endothelial cells.

•Provides detailed counts and density measurements for both pericytes and endothelial cells.

•Automatically stitches multiple partial retinal images into a complete, seamless image.

•Supports full image download for comprehensive analysis.

•Detects and locates the eyeball in five field-of-view fundus images of a single mouse.

•Removes background and stitches the images into a complete field-of-view.

•Offers fine-tuning capabilities for each partial image in the stitched output.

•Supports stitching and fine-tuning for both color and black-and-white fundus images.

• Detects and locates the eyeball in seven field-of-view fundus images of a cynomolgus monkey.

• Removes background and creates a complete stitched field-of-view image.

• Each partial image in the final stitched output supports fine-tuning.

• Compatible with color and black-and-white fundus images for accurate positioning and stitching.

• Automation: Reduces manual workload with precise, automated processes.

• Versatility: Supports multiple species and imaging modalities.

• Customization: Allows fine-tuning for enhanced accuracy and flexibility.

• Comprehensive Metrics: Delivers detailed quantitative insights for advanced analysis.

Our AI algorithms are engineered to meet the demands of modern ophthalmic research, ensuring unparalleled accuracy and efficiency in fundus imaging and analysis.