• DocumentCode
    3015796
  • Title

    Detection and labeling of retinal vessels for longitudinal studies

  • Author

    Wood, Sally L. ; Qu, Gongyuan ; Roloff, L.W.

  • Author_Institution
    Santa Clara Univ., CA, USA
  • Volume
    3
  • fYear
    1995
  • fDate
    23-26 Oct 1995
  • Firstpage
    164
  • Abstract
    Images of the retina taken as a routine opthalmologic procedure can provide early indications of damage to the retinal nerve fiber layer. Automatic processing of such images for screening is hindered by variable image acquisition and film processing parameters, and interference from the vessel structure in the image. This papers presents procedures for equalizing the image variability so that nonlinear morphological filtering methods can be used to locate and model vessel segments. Frequency domain analysis can then be used to assess texture parameters in the areas which do not include vessels
  • Keywords
    biomedical imaging; eye; feature extraction; filtering theory; frequency-domain analysis; image texture; mathematical morphology; medical image processing; neurophysiology; photographic applications; vision defects; automatic image processing; disease; early damage indications; film processing parameters; frequency domain analysis; glaucoma; image acquisition; image variability; longitudinal studies; nonlinear morphological filtering methods; photographic images; retina images; retinal nerve fiber layer; retinal vessel detection; retinal vessel labeling; routine opthalmologic procedure; screening; texture parameters; vessel segments; Biomedical optical imaging; Diseases; Image quality; Interference; Labeling; Lenses; Nerve fibers; Optical films; Retina; Retinal vessels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1995. Proceedings., International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-8186-7310-9
  • Type

    conf

  • DOI
    10.1109/ICIP.1995.537606
  • Filename
    537606