April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Inter- and Intra-observer agreement of Newly Developed Semi-automated Software for Retinal Artery-Vein Nicking Quantification and Severity Grading
Author Affiliations & Notes
  • Alauddin Bhuiyan
    Australian E-Health Research Centre, CSIRO Computational Informatics, Commonwealth Scientific and Industrial Research Organization (CSIRO), Floreat, WA, Australia
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, The University of Melbourne, Melbourne, VIC, Australia
  • Uyen Nguen
    Department of Computer Science and Information Systems, The University of Melbourne, Melbourne, VIC, Australia
  • Ryo Kawasaki
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, The University of Melbourne, Melbourne, VIC, Australia
  • Ecosse Luc Lamoureux
    Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, The University of Melbourne, Melbourne, VIC, Australia
    DUKE-NUS, Office of Clinical Sciences, Duke-NUS, Singapore, Singapore
  • Paul Mitchell
    Westmead Millennium Institute for Medical Research, University of Sydney, Sydney, NSW, Australia
  • Kotagiri Ramamohanarao
    Department of Computer Science and Information Systems, The University of Melbourne, Melbourne, VIC, Australia
  • Tien Y Wong
    Singapore Eye Research Institute, National University of Singapore, Singapore, Singapore
  • Yogesan Kanagasingam
    Australian E-Health Research Centre, CSIRO Computational Informatics, Commonwealth Scientific and Industrial Research Organization (CSIRO), Floreat, WA, Australia
  • Footnotes
    Commercial Relationships Alauddin Bhuiyan, None; Uyen Nguen, None; Ryo Kawasaki, None; Ecosse Lamoureux, None; Paul Mitchell, None; Kotagiri Ramamohanarao, None; Tien Wong, None; Yogesan Kanagasingam, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 234. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Alauddin Bhuiyan, Uyen Nguen, Ryo Kawasaki, Ecosse Luc Lamoureux, Paul Mitchell, Kotagiri Ramamohanarao, Tien Y Wong, Yogesan Kanagasingam; Inter- and Intra-observer agreement of Newly Developed Semi-automated Software for Retinal Artery-Vein Nicking Quantification and Severity Grading. Invest. Ophthalmol. Vis. Sci. 2014;55(13):234.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract
 
Purpose
 

To assess the reliability of novel computer based semi-automated software for quantifying the severity of retinal artery-vein nicking (AVN), a hypertensive retinopathy sign, from colour retinal photographs.

 
Methods
 

47 retinal photographs were randomly selected from the Singapore Malay Eye Study (SiMES), a population-based cross-sectional study of persons aged 40-80 years. A novel computer assisted software was developed to quantify retinal AVN by selecting vessel crossover region semi-automatically. The software then calculates the AVN values automatically. The accuracy was tested against the manually measured AVN severity level by expert grader through the Spearman rank correlation. Inter-grader and intra-session reliability were assessed by measurements from two individual graders and by grading two images of the same eye taken at different times, using Intra-class Correlation Coefficients (ICC).

 
Results
 

Accuracy measurements indicated a Spearman rank correlation (ρ) of 0.71 (p<0.01) between software measured AVN values and expert graders’ ranking on AVN severity. Between-grader and intra-session ICC value for AVN was 1, which indicates high repeatability of the proposed software for AVN severity measurement.

 
Conclusions
 

A novel semi-automatic measurement system for retinal artery vein nicking quantification is demonstrated for the first time. A good agreement with standard grading and excellent reproducibility, indicating that quantitative assessment of retinal AVN is possible. This can lead to achieve higher accuracy on CVD prediction model and early diagnosis of ocular diseases.

 
 
Graphical User Interface (GUI) for selected AVN region
 
Graphical User Interface (GUI) for selected AVN region
 
 
Resulting images for automated analysis and AVN quantification Computation
 
Resulting images for automated analysis and AVN quantification Computation
 
Keywords: 549 image processing • 551 imaging/image analysis: non-clinical • 688 retina  
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×