title: Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis.
abstract: OBJECTIVE
  To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method.
  
  
  METHODS
  This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal (24 images) and pathological (148 images) states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software ImageJ. Statistical analyses were performed for these groups using Microsoft Office Excel 2003 and GraphPad InStat software.
  
  
  RESULTS
  It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy (DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR (NPDR) images (segmented and skeletonized versions). The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images (segmented and skeletonized versions). The lowest values were found for the corresponding values of severe NPDR images (segmented and skeletonized versions).
  
  
  CONCLUSIONS
  The fractal analysis of fundus photographs may be used for a more complete undeTrstanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension. Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from healthy individuals.
authors: Discipline of Descriptive Geometry and Engineering Graphics, Department of AET, Faculty of Mechanical Engineering, Technical University of Cluj-Napoca, Cluj-Napoca 400641, Romania.
authors: Ştefan
authors: Ş
authors: Ţălu
authors: Discipline of Ophthalmology, Department of Surgical Specialties and Medical Imaging, Faculty of Medicine, Iuliu Haţieganu University of Medicine and Pharmacy Cluj-Napoca, Cluj-Napoca 400012, Romania.
authors: Dan Mihai
authors: DM
authors: Călugăru
authors: Department of Mathematics and Informatics, University of Palermo, Via Archirafi 34, Palermo 90123, Italy.
authors: Carmen Alina
authors: CA
authors: Lupaşcu
keywords: diabetic retinopathy; fractal; fractal dimension; retinal image analysis; retinal microvasculature