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School of Computer Science

Lincoln School of Computer Science
University of Lincoln
Brayford Pool
Lincoln
LN6 7TS
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Retinal vessel Segmentation

This page contains the material accompanying the paper: "DISCERN: A Generative Framework for Vessel Segmentation using convolutional neural networks and visual codebook" by Piotr Chudzik, Bashir Al-Diri, Francesco Caliva and Andrew Hunter.

We are providing two sets of results: raw vessel confidence maps and final results produced by thresholded confidence maps. For comparison purposes we attach results produced by best to date algorithm.

P. Liskowski and K. Krawiec, “Segmenting retinal blood vessels with deep neural networks,” IEEE Transactions on Medical Imaging, vol. PP,no. 99, pp. 1–1, 2016.

To download the results of DISCERN framework produced for DRIVE, STARE and CHASE_DB1 datasets, Please click here.

Or try this link Download

It contains results for three types of experiments: segmentation in presence of abnormality, cross-training and standard vessel segmentation. Each experiment contains images used for experiments, ground truth images, second marker results, FOV masks and DISCERN results.


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Dr. Bashir Al-Diri (PhD., MSc., BSc., FHEA)
Lincoln School of Computer Science
University of Lincoln
Brayford Pool
Lincoln LN6 7TS
United Kingdom
Email My Webpage Phone: +44 1522 837111
Fax: +44 1522 886974