Literature DB >> 8037918

Automated extraction and quantification of macular drusen from fundal photographs.

W H Morgan1, R L Cooper, I J Constable, R H Eikelboom.   

Abstract

The objective quantification of drusen (and other macular lesions) should have applications epidemiologically, in the study of the natural history of drusen, and with such instruments as the scanning laser ophthalmoscope. The automated extraction of drusen from photographs is technically difficult because of uneven macular reflectance, and the confusing pattern of darker vessels. We have developed a method using an IBM personal computer, an image digitising board and specially written software. Once the image is digitised, no further input from the operator is necessary. We present the results of manual counting versus automated counting on a small series of patients with drusen. The automated technique is highly reproducible, and will calculate the retinal area occupied by drusen. The area and numbers of drusen can be compared over time, giving an index of progression. Hard drusen are fairly well detected, but the detection of soft drusen with their lower contrast remains a problem. The technique cannot distinguish between drusen and other pale lesions (e.g., atrophic retinal changes).

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Year:  1994        PMID: 8037918     DOI: 10.1111/j.1442-9071.1994.tb01688.x

Source DB:  PubMed          Journal:  Aust N Z J Ophthalmol        ISSN: 0814-9763


  10 in total

1.  Automated, real time extraction of fundus images from slit lamp fundus biomicroscope video image sequences.

Authors:  B D Madjarov; J W Berger
Journal:  Br J Ophthalmol       Date:  2000-06       Impact factor: 4.638

2.  A method of drusen measurement based on reconstruction of fundus background reflectance.

Authors:  R T Smith; J K Chan; T Nagasaki; J R Sparrow; I Barbazetto
Journal:  Br J Ophthalmol       Date:  2005-01       Impact factor: 4.638

3.  Autofluorescence characteristics of normal foveas and reconstruction of foveal autofluorescence from limited data subsets.

Authors:  R Theodore Smith; Jan P Koniarek; Jackie Chan; Takayuki Nagasaki; Janet R Sparrow; Kevin Langton
Journal:  Invest Ophthalmol Vis Sci       Date:  2005-08       Impact factor: 4.799

4.  Automated detection of macular drusen using geometric background leveling and threshold selection.

Authors:  R Theodore Smith; Jackie K Chan; Takayuki Nagasaki; Umer F Ahmad; Irene Barbazetto; Janet Sparrow; Marta Figueroa; Joanna Merriam
Journal:  Arch Ophthalmol       Date:  2005-02

5.  Drusen analysis in a human-machine synergistic framework.

Authors:  R Theodore Smith; Mahsa A Sohrab; Nicole M Pumariega; Kanika Mathur; Raymond Haans; Anna Blonska; Karl Uy; Dominiek Despriet; Caroline Klaver
Journal:  Arch Ophthalmol       Date:  2011-01

6.  An interinstitutional comparative study and validation of computer aided drusen quantification.

Authors:  V Sivagnanavel; R T Smith; G B Lau; J Chan; C Donaldson; N V Chong
Journal:  Br J Ophthalmol       Date:  2005-05       Impact factor: 4.638

7.  Quantification of fluorescein-stained drusen associated with age-related macular degeneration.

Authors:  Duncan Friedman; John S Parker; James A Kimble; François C Delori; Gerald McGwin; Christine A Curcio
Journal:  Retina       Date:  2012-01       Impact factor: 4.256

8.  Automated drusen detection in retinal images using analytical modelling algorithms.

Authors:  André D Mora; Pedro M Vieira; Ayyakkannu Manivannan; José M Fonseca
Journal:  Biomed Eng Online       Date:  2011-07-12       Impact factor: 2.819

9.  A method of drusen measurement based on the geometry of fundus reflectance.

Authors:  R Theodore Smith; Takayuki Nagasaki; Janet R Sparrow; Irene Barbazetto; Caroline C W Klaver; Jackie K Chan
Journal:  Biomed Eng Online       Date:  2003-04-18       Impact factor: 2.819

10.  Automatic Screening and Grading of Age-Related Macular Degeneration from Texture Analysis of Fundus Images.

Authors:  Thanh Vân Phan; Lama Seoud; Hadi Chakor; Farida Cheriet
Journal:  J Ophthalmol       Date:  2016-04-14       Impact factor: 1.909

  10 in total

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