Synthetic Retinal Images from Unconditional GANs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU135167" target="_blank" >RIV/00216305:26230/19:PU135167 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8857857" target="_blank" >https://ieeexplore.ieee.org/document/8857857</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EMBC.2019.8857857" target="_blank" >10.1109/EMBC.2019.8857857</a>
Alternative languages
Result language
angličtina
Original language name
Synthetic Retinal Images from Unconditional GANs
Original language description
Synthesized retinal images are highly demanded in the development of automated eye applications since they can make machine learning algorithms more robust by increasing the size and heterogeneity of the training database. Recently, conditional Generative Adversarial Networks (cGANs) based synthesizers have been shown to be promising for generating retinal images. However, cGANs based synthesizers require segmented blood vessels (BV) along with RGB retinal images during training. The amount of such data (i.e., retinal images and their corresponding BV) available in public databases is very small. Therefore, for training cGANs, an extra system is necessary either for synthesizing BV or for segmenting BV from retinal images. In this paper, we show that by using unconditional GANs (uGANs) we can generate synthesized retinal images without using BV images.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society
ISBN
978-1-5386-1311-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
2736-2739
Publisher name
IEEE Computer Society
Place of publication
Berlin
Event location
Berlin
Event date
Jul 23, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000557295303038