Accuracy Assessment of Intra- and Intervisit Fundus Image Registration for Diabetic Retinopathy Screening

作者:Adal Kedir M*; van Etten Peter G; Martinez Jose P; van Vliet Lucas J; Vermeer Koenraad A
来源:Investigative Ophthalmology & Visual Science, 2015, 56(3): 1805-1812.
DOI:10.1167/iovs.14-15949

摘要

PURPOSE. We evaluated the accuracy of a recently developed fundus image registration method (Weighted Vasculature Registration, or WEVAR) and compared it to two top-ranked state-of-the-art commercial fundus mosaicking programs (i2k Retina, DualAlign LLC, and Merge Eye Care PACS, formerly named OIS AutoMontage) in the context of diabetic retinopathy (DR) screening. METHODS. Fundus images of 70 diabetic patients who visited the Rotterdam Eye Hospital in 2012 and 2013 for a DR screening program were registered by all three programs. The registration results were used to produce mosaics from fundus photos that were normalized for luminance and contrast to improve the visibility of small details. These mosaics subsequently were evaluated and ranked by two expert graders to assess the registration accuracy. RESULTS. Merge Eye Care PACS had high registration failure rates compared to WEVAR and i2k Retina (P = 8 x 10(-6) and P = 0.002, respectively). WEVAR showed significantly higher registration accuracy than i2k Retina in intravisit (P <= 0.0036) and intervisit (P <= 0.0002) mosaics. Therefore, fundus mosaics processed by WEVAR were more likely to have a higher score (odds ratio [OR] = 2.5, P = 10(-5) for intravisit and OR = 2.2, P = 0.006 for intervisit mosaics). WEVAR was preferred more often by the graders than i2k Retina (OR = 6.1, P = 7 x 10(-6)). CONCLUSIONS. WEVAR produced intra- and intervisit fundus mosaics with higher registration accuracy than Merge Eye Care PACS and i2k Retina. Merge Eye Care PACS had higher registration failures than the other two programs. Highly accurate registration methods, such as WEVAR, may potentially be used for more efficient human grading and in computer-aided screening systems for detecting DR progression.

  • 出版日期2015-3