Detail publikace

Synthetic Retinal Images from Unconditional GANs

BISWAS, S. ROHDIN, J. DRAHANSKÝ, M.

Originální název

Synthetic Retinal Images from Unconditional GANs

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

eye retina, blood vessels, GAN, synthetic image

Autoři

BISWAS, S.; ROHDIN, J.; DRAHANSKÝ, M.

Vydáno

23. 7. 2019

Nakladatel

IEEE Computer Society

Místo

Berlin

ISBN

978-1-5386-1311-5

Kniha

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society

Strany od

2736

Strany do

2739

Strany počet

4

URL

https://ieeexplore.ieee.org/document/8857857

BibTex

@inproceedings{BUT161844,
  author="Sangeeta {Biswas} and Johan Andréas {Rohdin} and Martin {Drahanský}",
  title="Synthetic Retinal Images from Unconditional GANs",
  booktitle="Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society",
  year="2019",
  pages="2736--2739",
  publisher="IEEE Computer Society",
  address="Berlin",
  doi="10.1109/EMBC.2019.8857857",
  isbn="978-1-5386-1311-5",
  url="https://ieeexplore.ieee.org/document/8857857"
}