Detail publikačního výsledku

Retinal Nerve Fiber Layer Analysis via Markov Random Fields Texture Modelling

ODSTRČILÍK, J.; KOLÁŘ, R.; HARABIŠ, V.; GAZÁREK, J.; JAN, J.

Originální název

Retinal Nerve Fiber Layer Analysis via Markov Random Fields Texture Modelling

Anglický název

Retinal Nerve Fiber Layer Analysis via Markov Random Fields Texture Modelling

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The texture analysis of the retinal nerve fiber layer (RNFL) in colour fundus images is a promising tool for early glau-coma diagnosis. This paper describes model-based method for detection of changes in the RNFL. The method utilizes Gaussian Markov random fields (GMRF) and the least-square error (LSE) estimate for the local RNFL texture modelling. The model parameters are used as a texture fea-tures and non-linear classifier based on the Bayesian rule is used for classification of healthy and glaucomatous RNFL tissue. The proposed features are tested in the sense of clas-sification errors and also they are applied for segmentation of RNFL defects in high-resolution colour fundus-camera images. The results are also compared with the Optical Co-herence Tomography images regarded as a gold standard for our application due to the possibility of RNFL thickness measurement.

Anglický abstrakt

The texture analysis of the retinal nerve fiber layer (RNFL) in colour fundus images is a promising tool for early glau-coma diagnosis. This paper describes model-based method for detection of changes in the RNFL. The method utilizes Gaussian Markov random fields (GMRF) and the least-square error (LSE) estimate for the local RNFL texture modelling. The model parameters are used as a texture fea-tures and non-linear classifier based on the Bayesian rule is used for classification of healthy and glaucomatous RNFL tissue. The proposed features are tested in the sense of clas-sification errors and also they are applied for segmentation of RNFL defects in high-resolution colour fundus-camera images. The results are also compared with the Optical Co-herence Tomography images regarded as a gold standard for our application due to the possibility of RNFL thickness measurement.

Klíčová slova

glaucoma, retinal nerve fiber layer, retinal vessels segmentation, texture analysis, pattern recognition

Klíčová slova v angličtině

glaucoma, retinal nerve fiber layer, retinal vessels segmentation, texture analysis, pattern recognition

Autoři

ODSTRČILÍK, J.; KOLÁŘ, R.; HARABIŠ, V.; GAZÁREK, J.; JAN, J.

Rok RIV

2011

Vydáno

24.08.2010

Nakladatel

EURASIP

Kniha

18th European Signal Processing Conference (EUSIPCO-2010)

Edice

EURASIP

ISSN

2076-1465

Periodikum

18th European Signal Processing Conference (EUSIPCO-2010)

Stát

Dánské království

Strany od

1650

Strany do

1654

Strany počet

4

BibTex

@inproceedings{BUT29969,
  author="Jan {Odstrčilík} and Radim {Kolář} and Vratislav {Harabiš} and Jiří {Gazárek} and Jiří {Jan}",
  title="Retinal Nerve Fiber Layer Analysis via Markov Random Fields Texture Modelling",
  booktitle="18th European Signal Processing Conference (EUSIPCO-2010)",
  year="2010",
  series="EURASIP",
  journal="18th European Signal Processing Conference (EUSIPCO-2010)",
  number="18",
  pages="1650--1654",
  publisher="EURASIP",
  issn="2076-1465"
}