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  • A method for segmentation of vessel structure in colour retinal fundus images is presented, based on 2D matched filtering correlating the local image areas with 2D masks obtained via averaging of brightness profiles of vessels for several different vessel widths. Each of the basic masks is rotated in twelve different directions. This way, 60 masks for 5 different widths, each with 12 orientations are produced and used as 2D convolution kernels of the matched filters. The maximum response of all the filter responses for a concrete local area thus carries, if there is a vessel present, the information both on the width and orientation of the vessel segment. Compared to the previously published results, the segmentation has been improved primarily in two directions: the width resolution has been increased from 3 to 5 classes with a better approximation of the brightness profiles, and the orientation information is now utilized to provide vessel direction maps that are further used in the following phase
  • A method for segmentation of vessel structure in colour retinal fundus images is presented, based on 2D matched filtering correlating the local image areas with 2D masks obtained via averaging of brightness profiles of vessels for several different vessel widths. Each of the basic masks is rotated in twelve different directions. This way, 60 masks for 5 different widths, each with 12 orientations are produced and used as 2D convolution kernels of the matched filters. The maximum response of all the filter responses for a concrete local area thus carries, if there is a vessel present, the information both on the width and orientation of the vessel segment. Compared to the previously published results, the segmentation has been improved primarily in two directions: the width resolution has been increased from 3 to 5 classes with a better approximation of the brightness profiles, and the orientation information is now utilized to provide vessel direction maps that are further used in the following phase (en)
Title
  • Improvement of Vessel Segmentation by Matched Filtering in Colour Retinal Images
  • Improvement of Vessel Segmentation by Matched Filtering in Colour Retinal Images (en)
skos:prefLabel
  • Improvement of Vessel Segmentation by Matched Filtering in Colour Retinal Images
  • Improvement of Vessel Segmentation by Matched Filtering in Colour Retinal Images (en)
skos:notation
  • RIV/00216305:26220/09:PU81701!RIV10-MSM-26220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0572), Z(MSM0021630513)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 318842
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/09:PU81701
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Retinal images, 2D matched filtering, vessel profiles, vessel segmentation. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E71B9B38BC72]
http://linked.open...v/mistoKonaniAkce
  • Mnichov
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • IFMBE Proceedings of World Congress on Medical Physics and Biomedical Engineering
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http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Gazárek, Jiří
  • Jan, Jiří
  • Kolář, Radim
  • Odstrčilík, Jan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-03897-6
http://localhost/t...ganizacniJednotka
  • 26220
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