Overview of Deep Learning Methods for Retinal Vessel Segmentation

Gorana Gojić, Ognjen Kundačina, Dragiša Mišković, Dinu Dragan
6/1/2023
eess.IVcs.CVcs.LG

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Abstract

Methods for automated retinal vessel segmentation play an important role in the treatment and diagnosis of many eye and systemic diseases. With the fast development of deep learning methods, more and more retinal vessel segmentation methods are implemented as deep neural networks. In this paper, we provide a brief review of recent deep learning methods from highly influential journals and conferences. The review objectives are: (1) to assess the design characteristics of the latest methods, (2) to report and analyze quantitative values of performance evaluation metrics, and (3) to analyze the advantages and disadvantages of the recent solutions.

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Cite this paper

@article{goji2023overview,
  title  = {Overview of Deep Learning Methods for Retinal Vessel Segmentation},
  author = {Gorana Gojić and Ognjen Kundačina and Dragiša Mišković and Dinu Dragan},
  year   = {2023},
  eprint = {2306.06116},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.06116v1}
}

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