Detail publikace

Simultaneous lesions and optic disc segmentation from ophthalmoscopic images

HESKO, B. et al.

Originální název

Simultaneous lesions and optic disc segmentation from ophthalmoscopic images

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this paper we present a novel approach to retina images segmentation. Simultaneously, 5 classes of objects are segmented including microaneurysms, haemorrhages, hard and soft exudates and optic disc. Segmentation of these eye disease symptoms is not straightforward, segmented objects are small, granular and may not be present in all images. We employ deep learning with fully convolutional methods. For a comparison, two different convolutional networks are used, SegNet and PSPNet. They are based on deep classifiers; therefore, we were able to use pretrained weights and only fine-tune both networks. Results suggest, we have chosen a perspective approach because we reached promising results.

Klíčová slova

deep learning, ophthalmology, retina images, segmentation

Autoři

HESKO, B. et al.

Vydáno

5. 10. 2018

Nakladatel

Katedra biomedicínskeho inžinierstva a merania

Místo

Kočice

ISBN

978-80-8086-271-8

Kniha

YBERC 2018 International Conference Proceedings

Strany od

1

Strany do

6

Strany počet

6

BibTex

@inproceedings{BUT150379,
  author="Branislav {Hesko} and Vratislav {Harabiš}",
  title="Simultaneous lesions and optic disc segmentation from ophthalmoscopic images",
  booktitle="YBERC 2018 International Conference Proceedings",
  year="2018",
  pages="1--6",
  publisher="Katedra biomedicínskeho inžinierstva a merania",
  address="Kočice",
  isbn="978-80-8086-271-8"
}