koriavinash1/Optic-Disk-Cup-Segmentation
Optic Disc and Optic Cup Segmentation using 57 layered deep convolutional neural network
This project helps ophthalmologists and optometrists analyze retinal fundus images for early glaucoma screening. It takes a fundus image as input and outputs segmented images highlighting the optic disk and optic cup, along with a classification indicating potential glaucoma. It is designed for medical professionals who need a tool to aid in diagnosing glaucoma.
No commits in the last 6 months.
Use this if you are a clinician or researcher who needs an automated tool to assist in segmenting optic disks and cups and screening for glaucoma from retinal fundus images.
Not ideal if you need a diagnostic tool that provides a definitive medical diagnosis rather than an assistive screening aid.
Stars
52
Forks
23
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 12, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/koriavinash1/Optic-Disk-Cup-Segmentation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
rsk97/Diabetic-Retinopathy-Detection
DIAGNOSIS OF DIABETIC RETINOPATHY FROM FUNDUS IMAGES USING SVM, KNN, and attention-based CNN...
cauchyturing/kaggle_diabetic_RAM
Extended Retinopathy Detection Challenge with the Regression Activation Map for visual explaination
JordiCorbilla/ocular-disease-intelligent-recognition-deep-learning
ODIR-2019: Ocular Disease Intelligent Recognition is a project leveraging state-of-the-art deep...
javathunderman/diabetic-retinopathy-screening
Diabetic retinopathy screening w/ Tensorflow.
TheBeastCoding/glaucoma-dataset-metadata
Actively maintained and comprehensive public glaucoma dataset catalog