Please use this identifier to cite or link to this item: https://doi.org/10.1109/TMI.2010.2076322
Title: Robust methodology for fractal analysis of the retinal vasculature
Authors: Azemin, M.Z.C.
Kumar, D.K.
Wong, T.Y. 
Kawasaki, R.
Mitchell, P.
Wang, J.J.
Keywords: Blue mountains eye study
eye fundus
Fourier fractal dimension (FFD)
Gabor wavelet
Issue Date: Feb-2011
Citation: Azemin, M.Z.C., Kumar, D.K., Wong, T.Y., Kawasaki, R., Mitchell, P., Wang, J.J. (2011-02). Robust methodology for fractal analysis of the retinal vasculature. IEEE Transactions on Medical Imaging 30 (2) : 243-250. ScholarBank@NUS Repository. https://doi.org/10.1109/TMI.2010.2076322
Abstract: We have developed a robust method to perform retinal vascular fractal analysis from digital retina images. The technique preprocesses the green channel retina images with Gabor wavelet transforms to enhance the retinal images. Fourier Fractal dimension is computed on these preprocessed images and does not require any segmentation of the vessels. This novel technique requires human input only at a single step; the allocation of the optic disk center. We have tested this technique on 380 retina images from healthy individuals aged 50+years, randomly selected from the Blue Mountains Eye Study population. To assess its reliability in assessing retinal vascular fractals from different allocation of optic center, we performed pair-wise Pearson correlation between the fractal dimension estimates with 100 simulated region of interest for each of the 380 images. There was Gaussian distribution variation in the optic center allocation in each simulation. The resulting mean correlation coefficient (standard deviation) was 0.93 (0.005). The repeatability of this method was found to be better than the earlier box-counting method. Using this method to assess retinal vascular fractals, we have also confirmed a reduction in the retinal vasculature complexity with aging, consistent with observations from other human organ systems. © 2010 IEEE.
Source Title: IEEE Transactions on Medical Imaging
URI: http://scholarbank.nus.edu.sg/handle/10635/109633
ISSN: 02780062
DOI: 10.1109/TMI.2010.2076322
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