Detail publikace

Analysis of the retinal nerve fiber layer texture related to the thickness measured by optical coherence tomography

Originální 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

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 the disease results in RNFL atrophy that can be detected as a shrinkage 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. The paper presents a novel approach of texture analysis enabling assessment of the RNFL thickness utilizing widely used colour fundus photographs. Our goal is to propose texture features useful for description of the variations in RNFL textural appearance related to the RNFL thickness changes. The evaluation part uses OCT as a gold standard for evaluation of the proposed features showing high correlation between the variations in RNFL texture and RNFL thickness 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 the disease results in RNFL atrophy that can be detected as a shrinkage 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. The paper presents a novel approach of texture analysis enabling assessment of the RNFL thickness utilizing widely used colour fundus photographs. Our goal is to propose texture features useful for description of the variations in RNFL textural appearance related to the RNFL thickness changes. The evaluation part uses OCT as a gold standard for evaluation of the proposed features showing high correlation between the variations in RNFL texture and RNFL thickness measured by OCT.

BibTex


@inproceedings{BUT100990,
  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 the disease results in RNFL atrophy that can be detected as a shrinkage 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. The paper presents a novel approach of texture analysis enabling assessment of the RNFL thickness utilizing widely used colour fundus photographs. Our goal is to propose texture features useful for description of the variations in RNFL textural appearance related to the RNFL thickness changes. The evaluation part uses OCT as a gold standard for evaluation of the proposed features showing high correlation between the variations in RNFL texture and RNFL thickness measured by OCT.",
  address="Taylor & Francis Group",
  booktitle="Computational Vision and Medical Image Processing IV",
  chapter="100990",
  edition="4",
  howpublished="print",
  institution="Taylor & Francis Group",
  year="2013",
  month="october",
  pages="105--110",
  publisher="Taylor & Francis Group",
  type="conference paper"
}