About: Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images     Goto   Sponge   NotDistinct   Permalink

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  • This paper proposes an automated image processing approach for detection of glaucoma which may be a diagnostic tool to help ophthalmologist in mass screening of glaucoma suspects. The proposed approach is based on the segmentation of optic disk and the optic cup and computing the cup-to-disc ratio. For segmentation of optic cup and optic disk, a double threshold method is used, one for removing blood vessels and background and second threshold for segmenting the super intensity pixels contained by the optic disk and optic cup. Further, Hough Transform is used to calculate the radius of optic disk and optic cup. The vertical cup to disk ratio is used as a parameter for identification of glaucoma symptoms in the fundus image. The results of the proposed method indicate that the approach is effective in glaucoma detection with better accuracy over existing methods.
  • This paper proposes an automated image processing approach for detection of glaucoma which may be a diagnostic tool to help ophthalmologist in mass screening of glaucoma suspects. The proposed approach is based on the segmentation of optic disk and the optic cup and computing the cup-to-disc ratio. For segmentation of optic cup and optic disk, a double threshold method is used, one for removing blood vessels and background and second threshold for segmenting the super intensity pixels contained by the optic disk and optic cup. Further, Hough Transform is used to calculate the radius of optic disk and optic cup. The vertical cup to disk ratio is used as a parameter for identification of glaucoma symptoms in the fundus image. The results of the proposed method indicate that the approach is effective in glaucoma detection with better accuracy over existing methods. (en)
Title
  • Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images
  • Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images (en)
skos:prefLabel
  • Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images
  • Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images (en)
skos:notation
  • RIV/00216305:26220/14:PU111155!RIV15-MSM-26220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 18390
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/14:PU111155
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Fundus image, super pixel, Neuroretinal Rim, optic nerve head, segmentation, boundary detection (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D43B80F63BA3]
http://linked.open...v/mistoKonaniAkce
  • Greater Noida
http://linked.open...i/riv/mistoVydani
  • Greater Noida
http://linked.open...i/riv/nazevZdroje
  • MEDCOM 2014 CD-ROM
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Burget, Radim
  • Říha, Kamil
  • Dutta, Malay Kishore
  • Singh, Anushikha
  • Parthasarathi, M.
  • Mourya, Amit Kumar
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-1-4799-5096-6
http://localhost/t...ganizacniJednotka
  • 26220
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