title: Detection of retinal capillary nonperfusion in fundus fluorescein angiogram of diabetic retinopathy.
abstract: BACKGROUND
  Retinal capillary nonperfusion (CNP) is one of the retinal vascular diseases in diabetic retinopathy (DR) patients. As there is no comprehensive detection technique to recognize CNP areas, we proposed a different method for computing detection of ischemic retina, non-perfused (NP) regions, in fundus fluorescein angiogram (FFA) images.
  
  
  METHODS
  Whilst major vessels appear as ridges, non-perfused areas are usually observed as ponds that are surrounded by healthy capillaries in FFA images. A new technique using homomorphic filtering to correct light illumination and detect the ponds surrounded in healthy capillaries on FFA images was designed and applied on DR fundus images. These images were acquired from the diabetic patients who had referred to the Nikookari hospital and were diagnosed for diabetic retinopathy during one year. Our strategy was screening the whole image with a fixed window size, which is small enough to enclose areas with identified topographic characteristics. To discard false nominees, we also performed a thresholding operation on the screen and marked images. To validate its performance we applied our detection algorithm on 41 FFA diabetic retinopathy fundus images in which the CNP areas were manually delineated by three clinical experts.
  
  
  RESULTS
  Lesions were found as smooth regions with very high uniformity, low entropy, and small intensity variations in FFA images. The results of automated detection method were compared with manually marked CNP areas so achieved sensitivity of 81%, specificity of 78%, and accuracy of 91%.The result was present as a Receiver operating character (ROC) curve, which has an area under the curve (AUC) of 0.796 with 95% confidence intervals.
  
  
  CONCLUSIONS
  This technique introduced a new automated detection algorithm to recognize non-perfusion lesions on FFA. This has potential to assist detecting and managing of ischemic retina and may be incorporated into automated grading diabetic retinopathy structures.
authors.affiliation: Department of Medical Bioengineering, Stem Cell Research Center, Tabriz University of Medical Sciences, Tabriz, Iran ; School of Medical Sciences, University of Aberdeen, Aberdeen, UK.
authors.forename: Seyed Hossein
authors.initials: SH
authors.lastname: Rasta
authors.affiliation: Department of Medical Bioengineering, Stem Cell Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
authors.forename: Shima
authors.initials: S
authors.lastname: Nikfarjam
authors.affiliation: Department of Ophthalmology, Tabriz University of Medical Sciences, Tabriz, Iran.
authors.forename: Alireza
authors.initials: A
authors.lastname: Javadzadeh
keywords: Capillary nonperfusion; Diabetic retinopathy; Diagnostic imaging; Fluorescein angiography; Image processing/analysis; Ischemic retina