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High-Resolution Fundus (HRF) Image Database

Introduction

This database has been established by a collaborative research group to support comparative studies on automatic segmentation algorithms on retinal fundus images. The database will be iteratively extended and the webpage will be improved.
We would like to help researchers in the evaluation of segmentation algorithms. We encourage anyone working with segmentation algorithms who found our database useful to send us their evaluation results with a reference to a paper where it is described. This way we can extend our database of algorithms with the given results to keep it always up-to-date.

The database can be used freely for research purposes. We release it under Creative Commons 4.0 Attribution License. If you are using our database to evaluate your methods, please cite

Budai, Attila; Bock, Rüdiger; Maier, Andreas; Hornegger, Joachim; Michelson, Georg. Robust Vessel Segmentation in Fundus Images. International Journal of Biomedical Imaging, vol. 2013, 2013

Data

Evaluation

A test version of an applet is available here to speed up the uploading and evaluation of images

Evaluation Results

Actual Content

Author
Dataset
Date
Sensitivity
Specificity
Accuracy
Calculation time*
Odstrcilik et. al.
[odstrcilik09]
Healthy images
2011-06-14
78.61% ± 3.92%
97.50% ± 0.65%
95.39% ± 0.61%
18 mins
Odstrcilik et. al.
[odstrcilik09]
Diabetic retinopathy images
2011-06-14
74.63% ± 5.66%
96.19% ± 0.77%
94.45% ± 0.84%
18 mins
Odstrcilik et. al.
[odstrcilik09]
Glaucomatous images
2011-06-14
79.00% ± 3.18%
96.38% ± 0.69%
94.97% ± 0.61%
18 mins

Preliminary Database

Author
Date
Sensitivity
Specificity
Accuracy
Calculation time*
Budai et. al.
[budai09]
2010-12-08
70.99% ± 4.00%
97.45% ± 0.44%
94.81% ± 0.60%
4 mins 40 secs
Odstrcilik et. al.
[odstrcilik09]
2010-12-08
81.65% ± 4.04%
96.09% ± 0.62%
94.48% ± 0.75%
18 mins
Blank result
(Everything is background)
2010-12-08
0.00% ± 0.00%
90.61% ± 0.93%
90.61% ± 0.93%
-

* Since the algorithms are tested on different hardwares using different programming languages and optimizations, the calculation times are rough approximations of the time needed to process a single image in average.

 

Contact

Responsible person for maintaining this homepage is:

Attila Budai

Responsible persons for the database are:

Attila Budai

Jan Odstrcilik

Acknowledgements

The database is provided by the Pattern Recognition Lab (CS5), the Department of Ophthalmology, Friedrich-Alexander University Erlangen-Nuremberg (Germany), and the Brno University of Technology, Faculty of Electrical Engineering and Comunnication, Department of Biomedical Engineering, Brno (Czech Republic).

This work has been supported by the national research center DAR (Data, Algorithms and Decision making) project no. 1M0572 coordinated by the Institute of Information Theory and Automation, Academy of Science, Czech Rep. and partly also by the institutional research frame no. MSM 0021630513; both grants sponsored by the Ministry of Education of the Czech Republic. The authors highly acknowledge the cooperation with the Eye Clinic Zlin, Czech Rep. (T. Kubena, M.D. and P. Cernosek, MSc), through which also the test set of images was provided.

Attila Budai is supported by the International Max Planck Research School for Optics and Imaging.

The authors gratefully acknowledge funding of the Erlangen Graduate School in Advanced Optical Technologies (SAOT) by the German National Science Foundation (DFG) in the framework of the excellence initiative.