Literature DB >> 20554610

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

Alan Wainwright1, Gerald Liew, George Burlutsky, Elena Rochtchina, Yong Ping Zhang, Wynne Hsu, Janice MongLi Lee, Tien Yin Wong, Paul Mitchell, Jie Jin Wang.   

Abstract

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.

Entities:  

Mesh:

Year:  2010        PMID: 20554610     DOI: 10.1167/iovs.09-4129

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  6 in total

1.  Fractal dimension of retinal vasculature as an image quality metric for automated fundus image analysis systems.

Authors:  Xingzheng Lyu; Purvish Jajal; Muhammad Zeeshan Tahir; Sanyuan Zhang
Journal:  Sci Rep       Date:  2022-07-13       Impact factor: 4.996

2.  Using Retinal Imaging to Study Dementia.

Authors:  Victor T T Chan; Tiffany H K Tso; Fangyao Tang; Clement Tham; Vincent Mok; Christopher Chen; Tien Y Wong; Carol Y Cheung
Journal:  J Vis Exp       Date:  2017-11-06       Impact factor: 1.355

3.  Reliability of Using Retinal Vascular Fractal Dimension as a Biomarker in the Diabetic Retinopathy Detection.

Authors:  Fan Huang; Behdad Dashtbozorg; Jiong Zhang; Erik Bekkers; Samaneh Abbasi-Sureshjani; Tos T J M Berendschot; Bart M Ter Haar Romeny
Journal:  J Ophthalmol       Date:  2016-09-14       Impact factor: 1.909

4.  Investigation of associations between retinal microvascular parameters and albuminuria in UK Biobank: a cross-sectional case-control study.

Authors:  Euan N Paterson; Chris Cardwell; Thomas J MacGillivray; Emanuele Trucco; Alexander S Doney; Paul Foster; Alexander P Maxwell; Gareth J McKay
Journal:  BMC Nephrol       Date:  2021-02-25       Impact factor: 2.388

5.  Zone specific fractal dimension of retinal images as predictor of stroke incidence.

Authors:  Behzad Aliahmad; Dinesh Kant Kumar; Hao Hao; Premith Unnikrishnan; Mohd Zulfaezal Che Azemin; Ryo Kawasaki; Paul Mitchell
Journal:  ScientificWorldJournal       Date:  2014-11-18

6.  Suitability of a Low-Cost, Handheld, Nonmydriatic Retinograph for Diabetic Retinopathy Diagnosis.

Authors:  Gwenolé Quellec; Loïc Bazin; Guy Cazuguel; Ivan Delafoy; Béatrice Cochener; Mathieu Lamard
Journal:  Transl Vis Sci Technol       Date:  2016-04-20       Impact factor: 3.283

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.