Detail publikace

Analysis of the Retinal Nerve Fiber Layer Texture Related to the Thickness Measured by Optical Coherence Tomography

ODSTRČILÍK, J. KOLÁŘ, R. TORNOW, R. BUDAI, A. JAN, J. MACKOVÁ, P. VODÁKOVÁ, M.

Originální název

Analysis of the Retinal Nerve Fiber Layer Texture Related to the Thickness Measured by Optical Coherence Tomography

Český název

Analysis of the Retinal Nerve Fiber Layer Texture Related to the Thickness Measured by Optical Coherence Tomography

Anglický název

Analysis of the Retinal Nerve Fiber Layer Texture Related to the Thickness Measured by Optical Coherence Tomography

Typ

kapitola v knize

Jazyk

en

Originální abstrakt

The retinal nerve fiber layer (RNFL) is one of the most affected retinal structures due to the glaucoma disease. Progression of this disease results in the RNFL atrophy that can be detected as the decrease of the layers thickness. Usually, the RNFL thickness can be assessed by optical coherence tomography (OCT). However, an examination using OCT is rather expensive and still not widely available. On the other hand, fundus camera is considered as a common and fundamental diagnostic device utilized at many ophthalmic facilities worldwide. This contribution presents a novel approach to texture analysis enabling assessment of the RNFL thickness in widely used colour fundus photographs. The aim is to propose a regression model based on different texture features effective for description of changes in the RNFL textural appearance related to the variations of RNFL thickness. The performance evaluation uses OCT as a gold standard modality for validation of the proposed approach. The results show high correlation between the models predicted output and RNFL thickness directly measured by OCT.

Český abstrakt

The retinal nerve fiber layer (RNFL) is one of the most affected retinal structures due to the glaucoma disease. Progression of this disease results in the RNFL atrophy that can be detected as the decrease of the layers thickness. Usually, the RNFL thickness can be assessed by optical coherence tomography (OCT). However, an examination using OCT is rather expensive and still not widely available. On the other hand, fundus camera is considered as a common and fundamental diagnostic device utilized at many ophthalmic facilities worldwide. This contribution presents a novel approach to texture analysis enabling assessment of the RNFL thickness in widely used colour fundus photographs. The aim is to propose a regression model based on different texture features effective for description of changes in the RNFL textural appearance related to the variations of RNFL thickness. The performance evaluation uses OCT as a gold standard modality for validation of the proposed approach. The results show high correlation between the models predicted output and RNFL thickness directly measured by OCT.

Anglický abstrakt

The retinal nerve fiber layer (RNFL) is one of the most affected retinal structures due to the glaucoma disease. Progression of this disease results in the RNFL atrophy that can be detected as the decrease of the layers thickness. Usually, the RNFL thickness can be assessed by optical coherence tomography (OCT). However, an examination using OCT is rather expensive and still not widely available. On the other hand, fundus camera is considered as a common and fundamental diagnostic device utilized at many ophthalmic facilities worldwide. This contribution presents a novel approach to texture analysis enabling assessment of the RNFL thickness in widely used colour fundus photographs. The aim is to propose a regression model based on different texture features effective for description of changes in the RNFL textural appearance related to the variations of RNFL thickness. The performance evaluation uses OCT as a gold standard modality for validation of the proposed approach. The results show high correlation between the models predicted output and RNFL thickness directly measured by OCT.

Klíčová slova

glaucoma, retinal nerve fiber layer, texture analysis, fundus images, local binary patterns, markov random fields

Vydáno

01.05.2015

Nakladatel

Springer International Publishing

Místo

Switzerland

ISBN

978-3-319-13406-2

Kniha

Developments in Medical Image Processing and Computational Vision

Edice

Lecture Notes in Computational Vision and Biomechanics

Číslo edice

19

Strany od

19

Strany do

40

Strany počet

22

BibTex


@inbook{BUT114386,
  author="Jan {Odstrčilík} and Radim {Kolář} and Ralf-Peter {Tornow} and Attila {Budai} and Jiří {Jan} and Pavlína {Macková} and Martina {Vodáková}",
  title="Analysis of the Retinal Nerve Fiber Layer Texture Related to the Thickness Measured by Optical Coherence Tomography",
  annote="The retinal nerve fiber layer (RNFL) is one of the most affected retinal structures due to the glaucoma disease. Progression of this disease results in the RNFL atrophy that can be detected as the decrease of the layers thickness. Usually, the RNFL thickness can be assessed by optical coherence tomography (OCT). However, an examination using OCT is rather expensive and still not widely available. On the other hand, fundus camera is considered as a common and fundamental diagnostic device utilized at many ophthalmic facilities worldwide. This contribution presents a novel approach to texture analysis enabling assessment of the RNFL thickness in widely used colour fundus photographs. The aim is to propose a regression model based on different texture features effective for description of changes in the RNFL textural appearance related to the variations of RNFL thickness. The performance evaluation uses OCT as a gold standard modality for validation of the proposed approach. The results show high correlation between the models predicted output and RNFL thickness directly measured by OCT.",
  address="Springer International Publishing",
  booktitle="Developments in Medical Image Processing and Computational Vision",
  chapter="114386",
  doi="10.1007/978-3-319-13407-9",
  edition="Lecture Notes in Computational Vision and Biomechanics",
  howpublished="print",
  institution="Springer International Publishing",
  year="2015",
  month="may",
  pages="19--40",
  publisher="Springer International Publishing",
  type="book chapter"
}