title: Fractal analysis of the retinal vascular network in fundus images.
abstract: Complexity of the retinal vascular network is quantified through the measurement of fractal dimension. A computerized approach enhances and segments the retinal vasculature in digital fundus images with an accuracy of 94% in comparison to the gold standard of manual tracing. Fractal analysis was performed on skeletonized versions of the network in 40 images from a study of stroke. Mean fractal dimension was found to be 1.398 (with standard deviation 0.024) from 20 images of the hypertensives sub-group and 1.408 (with standard deviation 0.025) from 18 images of the non-hypertensives subgroup. No evidence of a significant difference in the results was found for this sample size. However, statistical analysis showed that to detect a significant difference at the level seen in the data would require a larger sample size of 88 per group.
authors.affiliation: Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK. t.j.macgillivray@ed.ac.uk
authors.forename: T J
authors.initials: TJ
authors.lastname: Macgillivray
authors.forename: N
authors.initials: N
authors.lastname: Patton
authors.forename: F N
authors.initials: FN
authors.lastname: Doubal
authors.forename: C
authors.initials: C
authors.lastname: Graham
authors.forename: J M
authors.initials: JM
authors.lastname: Wardlaw
mesh_terms: D017709:Fractals; D006801:Humans; D006973:Hypertension / Q000473:pathology; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D012171:Retinal Vessels / Q000473:pathology*; D020521:Stroke / Q000473:pathology