DocumentCode :
1857060
Title :
Fractal analysis of the retinal vascular network in fundus images
Author :
MacGillivray, T.J. ; Patton, N. ; Doubal, F.N. ; Graham, C. ; Wardlaw, J.M.
Author_Institution :
Univ. of Edinburgh, Edinburgh
fYear :
2007
fDate :
22-26 Aug. 2007
Firstpage :
6455
Lastpage :
6458
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.
Keywords :
biomedical measurement; biomedical optical imaging; blood vessels; eye; fractals; haemodynamics; image enhancement; image segmentation; medical image processing; statistical analysis; digital fundus images; fractal analysis; fractal dimension measurement; hypertension; image enhancement; image segmentation; retinal vascular network; statistical analysis; stroke; Bismuth; Filtering; Fractals; Hospitals; Image analysis; Image processing; Image reconstruction; Image segmentation; Lighting; Retina; Fractals; Humans; Hypertension; Image Interpretation, Computer-Assisted; Retinal Vessels; Stroke;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
ISSN :
1557-170X
Print_ISBN :
978-1-4244-0787-3
Type :
conf
DOI :
10.1109/IEMBS.2007.4353837
Filename :
4353837
Link To Document :
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