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Deep Retinal Image Understanding (DRIU)

State of the art in retinal vessel and optic disc segmentation


Publications

MICCAI

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 = {K.K. Maninis and J. Pont-Tuset and P. Arbel\'{a}ez and L. Van Gool},
title = {Deep Retinal Image Understanding},
booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
year = {2016}
}
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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.