Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database

Odstrcilik J, Kolar R, Budai A, Hornegger J, Jan J, Gazarek J, Kubena T, Cernosek P, Svoboda O, Angelopoulou E (2013)

Publication Status: Published

Publication Type: Journal article

Publication year: 2013

Journal

IET Image Processing Institution of Engineering and Technology (IET)

Publisher: Institution of Engineering and Technology (IET)

Book Volume: 7

Pages Range: 373-383

Journal Issue: 4

DOI: 10.1049/iet-ipr.2012.0455

Abstract

Automatic assessment of retinal vessels plays an important role in the diagnosis of various eye, as well as systemic diseases. A public screening is highly desirable for prompt and effective treatment, since such diseases need to be diagnosed at an early stage. Automated and accurate segmentation of the retinal blood vessel tree is one of the challenging tasks in the computer-aided analysis of fundus images today. We improve the concept of matched filtering, and propose a novel and accurate method for segmenting retinal vessels. Our goal is to be able to segment blood vessels with varying vessel diameters in high-resolution colour fundus images. All recent authors compare their vessel segmentation results to each other using only low-resolution retinal image databases. Consequently, we provide a new publicly available high-resolution fundus image database of healthy and pathological retinas. Our performance evaluation shows that the proposed blood vessel segmentation approach is at least comparable with recent state-of-the-art methods. It outperforms most of them with an accuracy of 95% evaluated on the new database.

Authors with CRIS profile

Attila Budai Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Joachim Hornegger Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Elli Angelopoulou Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung)

Involved external institutions

Brno University of Technology (BUT) / Vysoké učení technické v Brně (VUT) CZ Czech Republic (CZ) Ophthalmology Clinic M.D. Tomas Kubena CZ Czech Republic (CZ)

How to cite

APA:

Odstrcilik, J., Kolar, R., Budai, A., Hornegger, J., Jan, J., Gazarek, J.,... Angelopoulou, E. (2013). Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database. IET Image Processing, 7(4), 373-383. https://doi.org/10.1049/iet-ipr.2012.0455

MLA:

Odstrcilik, Jan, et al. "Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database." IET Image Processing 7.4 (2013): 373-383.

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