Publication detail

Synthetic Retinal Images from Unconditional GANs

BISWAS, S. ROHDIN, J. DRAHANSKÝ, M.

Original Title

Synthetic Retinal Images from Unconditional GANs

Type

conference paper

Language

English

Original Abstract

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.

Keywords

eye retina, blood vessels, GAN, synthetic image

Authors

BISWAS, S.; ROHDIN, J.; DRAHANSKÝ, M.

Released

23. 7. 2019

Publisher

IEEE Computer Society

Location

Berlin

ISBN

978-1-5386-1311-5

Book

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

Pages from

2736

Pages to

2739

Pages count

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"
}