Detail publikace

Towards automated diagnostic evaluation of retina images

Originální název

Towards automated diagnostic evaluation of retina images

Anglický název

Towards automated diagnostic evaluation of retina images

Jazyk

en

Originální abstrakt

In this paper we address automatic segmentation of the optic nerve head (ONH) with the long-term goal of automatic diagnosis of the early stages of glaucoma. The images discussed are average images obtained from a scanning laser ophthalmoscope (SLO). The segmentation consists of the following main steps: finding a region of interest containing the ONH, constraining the search space for final segmentation, and computing the fine segmentation by an active contour model. The agreement of “true positive pixels,” i.e., pixels attributed to the ONH by both manual and automatic segmentation, is very good. The classification results obtained from three different classifiers using manual or automatic segmentation still reveal the superiority of manual segmentation. One means to further improve automatic segmentation is to use information from an SLO as well as from a fundus camera.

Anglický abstrakt

In this paper we address automatic segmentation of the optic nerve head (ONH) with the long-term goal of automatic diagnosis of the early stages of glaucoma. The images discussed are average images obtained from a scanning laser ophthalmoscope (SLO). The segmentation consists of the following main steps: finding a region of interest containing the ONH, constraining the search space for final segmentation, and computing the fine segmentation by an active contour model. The agreement of “true positive pixels,” i.e., pixels attributed to the ONH by both manual and automatic segmentation, is very good. The classification results obtained from three different classifiers using manual or automatic segmentation still reveal the superiority of manual segmentation. One means to further improve automatic segmentation is to use information from an SLO as well as from a fundus camera.

BibTex


@article{BUT46311,
  author="Radim {Chrástek} and Libor {Kubečka} and Jiří {Jan}",
  title="Towards automated diagnostic evaluation of retina images",
  annote="In this paper we address automatic segmentation of the optic nerve head (ONH) with the long-term
goal of automatic diagnosis of the early stages of glaucoma. The images discussed are average images obtained
from a scanning laser ophthalmoscope (SLO). The segmentation consists of the following main steps: finding
a region of interest containing the ONH, constraining the search space for final segmentation, and computing
the fine segmentation by an active contour model. The agreement of “true positive pixels,” i.e., pixels attributed
to the ONH by both manual and automatic segmentation, is very good. The classification results obtained from
three different classifiers using manual or automatic segmentation still reveal the superiority of manual segmentation.
One means to further improve automatic segmentation is to use information from an SLO as well as from
a fundus camera.",
  address="MAIK Nauka/Interperiodica Publishing, Moscow",
  chapter="46311",
  institution="MAIK Nauka/Interperiodica Publishing, Moscow",
  journal="Pattern Recognition and Image Analysis
",
  number="2",
  volume="15",
  year="2005",
  month="january",
  pages="273",
  publisher="MAIK Nauka/Interperiodica Publishing, Moscow",
  type="journal article - other"
}