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KÖHLER, T. BUDAI, A. KRAUS, M. ODSTRČILÍK, J. MICHELSON, G. HORNEGGER, J.
Original Title
Automatic no-reference quality assessment for retinal fundus images using vessel segmentation
Type
conference paper
Language
English
Original Abstract
Fundus imaging is the most commonly used modality to collect information about the human eye background. Objective and quantitative assessment of quality for the acquired images is essential for manual, computer-aided and fully automatic diagnosis. In this paper, we present a noreference quality metric to quantify image noise and blur and its application to fundus image quality assessment. The proposed metric takes the vessel tree visible on the retina as guidance to determine an image quality score. In our experiments, the performance of this approach is demonstrated by correlation analysis with the established full-reference metrics peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM). We found a Spearman rank correlation for PSNR and SSIM of 0.89 and 0.91. For real data, our metric correlates reasonable to a human observer, indicating high agreement to human visual perception.
Keywords
fundus images, image quality assesment, fundus camera, blood vessel segmentation
Authors
KÖHLER, T.; BUDAI, A.; KRAUS, M.; ODSTRČILÍK, J.; MICHELSON, G.; HORNEGGER, J.
RIV year
2013
Released
20. 6. 2013
Publisher
University of Porto
Location
Porto, Portugalsko
ISBN
978-1-4799-1053-3
Book
26th IEEE International Symposium on Computer-Based Medical Systems
Edition
26
Pages from
95
Pages to
100
Pages count
6
BibTex
@inproceedings{BUT99737, author="Thomas {Köhler} and Attila {Budai} and Martin {Kraus} and Jan {Odstrčilík} and Georg {Michelson} and Joachim {Hornegger}", title="Automatic no-reference quality assessment for retinal fundus images using vessel segmentation", booktitle="26th IEEE International Symposium on Computer-Based Medical Systems", year="2013", series="26", pages="95--100", publisher="University of Porto", address="Porto, Portugalsko", isbn="978-1-4799-1053-3" }