Publications
K.K. Maninis,
J. Pont-Tuset,
P. Arbeláez, and
L. Van Gool
Deep Retinal Image Understanding
Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2016
[PDF] [Supplemental] [BibTex]
@inproceedings{Man+16,
author = {Kevis-Kokitsi Maninis and Jordi Pont-Tuset and Pablo Arbel\'{a}ez and Luc Van Gool},
title = {Deep Retinal Image Understanding},
booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
year = {2016}
}
Abstract
This paper presents Deep Retinal Image Understanding (DRIU), a unified framework of retinal image analysis that provides both retinal vessel and optic disc segmentation using deep Convolutional Neural Networks (CNNs). We show both qualitative and quantitative experimental validation in four public datasets, on which DRIU presents super-human performance.
Click on the image to see DRIU detections
Benchmark State-of-the-Art
Display the evaluation of the current State-of-the-Art retinal vessel and optic disc segmentation techniques.
Explore State-of-the-Art Results
Visualize the segmentation results for all state-of-the-Art techniques on all testing images of DRIVE, STARE, DRIONS-DB and RIM-ONE-r3 datasets.
Downloads
Download the pre-computed results from DRIU, as well as all other techniques.