Using an Image Fusion Methodology to Improve Efficiency and Traceability of Posterior Pole Vessel Analysis by ROPtool.

Journal Article

The diagnosis of plus disease in retinopathy of prematurity (ROP) largely determines the need for treatment; however, this diagnosis is subjective. To make the diagnosis of plus disease more objective, semi-automated computer programs (e.g. ROPtool) have been created to quantify vascular dilation and tortuosity. ROPtool can accurately analyze blood vessels only in images with very good quality, but many still images captured by indirect ophthalmoscopy have insufficient image quality for ROPtool analysis.To evaluate the ability of an image fusion methodology (robust mosaicing) to increase the efficiency and traceability of posterior pole vessel analysis by ROPtool.We retrospectively reviewed video indirect ophthalmoscopy images acquired during routine ROP examinations and selected the best unenhanced still image from the video for each infant. Robust mosaicing was used to create an enhanced mosaic image from the same video for each eye. We evaluated the time required for ROPtool analysis as well as ROPtool's ability to analyze vessels in enhanced vs. unenhanced images.We included 39 eyes of 39 infants. ROPtool analysis was faster (125 vs. 152 seconds; p=0.02) in enhanced vs. unenhanced images, respectively. ROPtool was able to trace retinal vessels in more quadrants (143/156, 92% vs 115/156, 74%; p=0.16) in enhanced mosaic vs. unenhanced still images, respectively and in more overall (38/39, 97% vs. 34/39, 87%; p=0.07) enhanced mosaic vs. unenhanced still images, respectively.Retinal image enhancement using robust mosaicing advances efforts to automate grading of posterior pole disease in ROP.

Full Text

Duke Authors

Cited Authors

  • Prakalapakorn, SG; Vickers, LA; Estrada, R; Freedman, SF; Tomasi, C; Farsiu, S; Wallace, DK

Published Date

  • January 2017

Published In

Volume / Issue

  • 11 /

Start / End Page

  • 143 - 151

PubMed ID

  • 28761567

Electronic International Standard Serial Number (EISSN)

  • 1874-3641

International Standard Serial Number (ISSN)

  • 1874-3641

Digital Object Identifier (DOI)

  • 10.2174/1874364101711010143

Language

  • eng