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Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension.

Publication ,  Journal Article
Wainwright, A; Liew, G; Burlutsky, G; Rochtchina, E; Zhang, YP; Hsu, W; Lee, JM; Wong, TY; Mitchell, P; Wang, JJ
Published in: Invest Ophthalmol Vis Sci
November 2010

PURPOSE: Fractal dimension of retinal vasculature is a global summary measure of retinal vascular network pattern and geometry. This study was conducted to examine the effect of variations in image color, brightness, focus, contrast, and format on the measurement of retinal vascular fractal dimension. METHODS: A set of 30 retinal images from the Blue Mountains Eye Study was used for a series of experiments by varying brightness, focus (blur), contrast, and color (color versus monochrome). The original and the modified images were graded for fractal dimension (D(f)) using dedicated retinal imaging software (IRIS-Fractal). A further set of 20 grayscale images was used to compare image format (.jpg versus .tif) with regard to the resultant D(f) and processing time. RESULTS: The mean D(f) of original images in this sample was 1.454. Compared with the original set of images, variations in brightness, focus, contrast, and color affected the measurements to a small to moderate degree (Pearson correlation coefficient, r, ranged from 0.47 to 0.97). Very dark or blurry images resulted in a substantially lower estimate of D(f). Monochrome images were also consistently associated with lower D(f) compared with that obtained from color images. Using .jpg or .tif image formats did not affect the measurement or the time needed to process and measure D(f). CONCLUSIONS: Variations in image brightness, focus, and contrast can significantly affect the measurement of retinal vascular fractals. Standardization of image parameters and consistent use of either monochrome or color images would reduce measurement noise and enhance the comparability of the results.

Duke Scholars

Published In

Invest Ophthalmol Vis Sci

DOI

EISSN

1552-5783

Publication Date

November 2010

Volume

51

Issue

11

Start / End Page

5525 / 5529

Location

United States

Related Subject Headings

  • Retinal Vessels
  • Reproducibility of Results
  • Photography
  • Ophthalmology & Optometry
  • Image Processing, Computer-Assisted
  • Image Enhancement
  • Humans
  • Fractals
  • Color
  • 3212 Ophthalmology and optometry
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Wainwright, A., Liew, G., Burlutsky, G., Rochtchina, E., Zhang, Y. P., Hsu, W., … Wang, J. J. (2010). Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension. Invest Ophthalmol Vis Sci, 51(11), 5525–5529. https://doi.org/10.1167/iovs.09-4129
Wainwright, Alan, Gerald Liew, George Burlutsky, Elena Rochtchina, Yong Ping Zhang, Wynne Hsu, Janice MongLi Lee, Tien Yin Wong, Paul Mitchell, and Jie Jin Wang. “Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension.Invest Ophthalmol Vis Sci 51, no. 11 (November 2010): 5525–29. https://doi.org/10.1167/iovs.09-4129.
Wainwright A, Liew G, Burlutsky G, Rochtchina E, Zhang YP, Hsu W, et al. Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension. Invest Ophthalmol Vis Sci. 2010 Nov;51(11):5525–9.
Wainwright, Alan, et al. “Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension.Invest Ophthalmol Vis Sci, vol. 51, no. 11, Nov. 2010, pp. 5525–29. Pubmed, doi:10.1167/iovs.09-4129.
Wainwright A, Liew G, Burlutsky G, Rochtchina E, Zhang YP, Hsu W, Lee JM, Wong TY, Mitchell P, Wang JJ. Effect of image quality, color, and format on the measurement of retinal vascular fractal dimension. Invest Ophthalmol Vis Sci. 2010 Nov;51(11):5525–5529.

Published In

Invest Ophthalmol Vis Sci

DOI

EISSN

1552-5783

Publication Date

November 2010

Volume

51

Issue

11

Start / End Page

5525 / 5529

Location

United States

Related Subject Headings

  • Retinal Vessels
  • Reproducibility of Results
  • Photography
  • Ophthalmology & Optometry
  • Image Processing, Computer-Assisted
  • Image Enhancement
  • Humans
  • Fractals
  • Color
  • 3212 Ophthalmology and optometry