beasygo1ng/OCT-Retinal-Layer-Segmenter
UNet based model that segment retina to 8 layers in OCT images
This tool helps ophthalmologists and researchers automatically analyze Optical Coherence Tomography (OCT) scans of the retina. It takes a grayscale OCT image as input and outputs a segmented image that highlights eight distinct retinal layers. This automation aims to speed up the identification of eye diseases like diabetic macular edema and age-related macular degeneration by providing precise measurements of retinal layer thickness.
No commits in the last 6 months.
Use this if you need to quickly and accurately segment retinal layers from OCT images to aid in disease diagnosis and monitoring.
Not ideal if you are working with OCT images that are significantly different from the fovea-centered, 750x500 pixel grayscale images of healthy patients used for training, as performance may vary.
Stars
85
Forks
7
Language
Jupyter Notebook
License
—
Category
Last pushed
Apr 22, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/beasygo1ng/OCT-Retinal-Layer-Segmenter"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
dipy/dipy
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for...
Project-MONAI/MONAI
AI Toolkit for Healthcare Imaging
Project-MONAI/MONAILabel
MONAI Label is an intelligent open source image labeling and learning tool.
neuronets/nobrainer
A framework for developing neural network models for 3D image processing.
axondeepseg/axondeepseg
Axon/Myelin segmentation using Deep Learning