Automatic no-reference quality assessment for retinal fundus images using vessel segmentation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU103693" target="_blank" >RIV/00216305:26220/13:PU103693 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Automatic no-reference quality assessment for retinal fundus images using vessel segmentation
Original language description
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. Inour 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/7AMB12DE002" target="_blank" >7AMB12DE002: Extraction of novel disease specific features from fundus images</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
26th IEEE International Symposium on Computer-Based Medical Systems
ISBN
978-1-4799-1053-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
95-100
Publisher name
University of Porto
Place of publication
Porto, Portugalsko
Event location
Porto, Portugalsko
Event date
Jun 20, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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