Detail publikace

Segmentation of optic disc and cup in retinal images using of deep learning approaches

NOHEL, M. KOLÁŘ, R.

Originální název

Segmentation of optic disc and cup in retinal images using of deep learning approaches

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

This paper presents a comparative analysis of optic disc and cup segmentation in retinal fundus images using two deep learning models: the classical U-net and its modified version, nnU-Net. The models were trained and tested on publicly available databases consisting of 1295 images for training and 555 images for testing. The results indicate that while nnU-Net demonstrated only slight improvements in disc segmentation on the test database, it significantly outperformed the U-net model in optical cup segmentation.

Klíčová slova

deep learning, convolutional neural networks, vertebrae segmentation, segmentation, spine, vertebra, CT, computed tomography

Autoři

NOHEL, M.; KOLÁŘ, R.

Vydáno

25. 4. 2023

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Communication

Místo

Brno, Czech Republic

ISBN

978-80-214-6153-6

Kniha

Proceedings I of the 29th Conference STUDENT EEICT 2023

Edice

1st edition

Strany od

265

Strany do

269

Strany počet

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf

BibTex

@inproceedings{BUT184277,
  author="Michal {Nohel} and Radim {Kolář}",
  title="Segmentation of optic disc and cup in retinal images using of deep learning approaches",
  booktitle="Proceedings I of the 29th Conference STUDENT EEICT 2023",
  year="2023",
  series="1st edition",
  pages="265--269",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno, Czech Republic",
  isbn="978-80-214-6153-6",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf"
}