Fractal analysis of neovascularization due to diabetic retinopathy in retinal fundus images

This study focuses on detecting and classifying neovascularization caused by proliferative diabetic retinopathy (PDR) in retinal fundus images. Image processing methods were applied to detect retinal vessels. A fractal analysis approach based on the box-counting method was used to quantify vascular patterns in normal and abnormal cases showing neovascularization near the optic disk (NVD). Ten images including five normal cases and five neovascularization cases were analyzed. The mean fractal dimension obtained for the NVD cases was 1.66 compared to the mean value of 1.52 for the normal cases. The statistical significance of the difference was high, with a p-value of 0.0088. The results show promise for use in detecting neovascularization in retinal images caused by PDR.

[1]  Rangaraj M. Rangayyan,et al.  Detection of blood vessels in the retina with multiscale Gabor filters , 2008, J. Electronic Imaging.

[2]  P. Mitchell,et al.  The retinal vasculature as a fractal: methodology, reliability, and relationship to blood pressure. , 2008, Ophthalmology.

[3]  Jason Noble,et al.  Diabetic retinopathy , 2010, Canadian Medical Association Journal.

[4]  Marios S. Pattichis,et al.  Detection of neovascularization in the optic disc using an AM-FM representation, granulometry, and vessel segmentation , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  A. Goldberger Fractal mechanisms in the electrophysiology of the heart , 1992, IEEE Engineering in Medicine and Biology Magazine.

[6]  A. Daxer,et al.  The fractal geometry of proliferative diabetic retinopathy: implications for the diagnosis and the process of retinal vasculogenesis. , 1993, Current eye research.

[7]  Tien Yin Wong,et al.  Retinal vascular fractals and microvascular and macrovascular complications in type 1 diabetes. , 2010, Ophthalmology.

[8]  Rangaraj M. Rangayyan,et al.  Detection of Blood Vessels in Retinal Fundus Images , 2014, Comput. Sci. J. Moldova.

[9]  David B. L. Bong,et al.  Detection of Neovascularization in Diabetic Retinopathy , 2012, Journal of Digital Imaging.

[10]  Bruce J. West,et al.  Chaos and fractals in human physiology. , 1990, Scientific American.

[11]  Rangaraj M. Rangayyan,et al.  Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis , 2010, Journal of Digital Imaging.

[12]  Rangaraj M. Rangayyan,et al.  Fractal Analysis of Contours of Breast Masses in Mammograms , 2007, Journal of Digital Imaging.

[13]  Bruce J. West,et al.  Fractal physiology , 1994, IEEE Engineering in Medicine and Biology Magazine.

[14]  M. Usman Akram,et al.  Detection of Neovascularization for Screening of Proliferative Diabetic Retinopathy , 2012, ICIAR.

[15]  T. Wong,et al.  Quantitative Assessment of Early Diabetic Retinopathy Using Fractal Analysis , 2009, Diabetes Care.

[16]  T. MacGillivray,et al.  Fractal analysis of the retinal vascular network in fundus images , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[17]  R. Jain,et al.  Fractal Characteristics of Tumor Vascular Architecture During Tumor Growth and Regression , 1997, Microcirculation.

[18]  Alicia J. Jenkins,et al.  Retinal Vascular Fractal Dimension and Risk of Early Diabetic Retinopathy , 2009, Diabetes Care.

[19]  S. Duke-Elder,et al.  Parsons' Diseases of the Eye , 1990 .

[20]  A. Daxer Characterisation of the neovascularisation process in diabetic retinopathy by means of fractal geometry: diagnostic implications , 1993, Graefe's Archive for Clinical and Experimental Ophthalmology.

[21]  Rangaraj M. Rangayyan,et al.  Fractal Analysis of Breast Masses in Mammograms , 2012, Fractal Analysis of Breast Masses in Mammograms.

[22]  R. Rangayyan Biomedical Image Analysis , 2004 .

[23]  J. V. van Beek,et al.  Four methods to estimate the fractal dimension from self-affine signals (medical application) , 1992, IEEE Engineering in Medicine and Biology Magazine.

[24]  Rangaraj M. Rangayyan,et al.  Ophthalmological Imaging and Applications , 2014 .

[25]  M. Cree,et al.  Automated Image Detection of Retinal Pathology , 2009 .

[26]  B. Zee,et al.  Detection of Neovascularization Based on Fractal and Texture Analysis with Interaction Effects in Diabetic Retinopathy , 2013, PloS one.

[27]  John I. Clark,et al.  Fractal analysis of region-based vascular change in the normal and non-proliferative diabetic retina , 2002, Current eye research.

[28]  R. Kumaresan,et al.  Fractal dimension in the analysis of medical images , 1992, IEEE Engineering in Medicine and Biology Magazine.

[29]  Rangaraj M. Rangayyan,et al.  Computer-aided Diagnosis of Proliferative Diabetic Retinopathy via Modeling of the Major Temporal Arcade in Retinal Fundus Images , 2013, Journal of Digital Imaging.

[30]  Herbert F Jelinek,et al.  Automated segmentation of retinal blood vessels and identification of proliferative diabetic retinopathy. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[31]  D. M. Gordon Diseases of the Eye , 1918, Clinical symposia.

[32]  Peter F. Sharp,et al.  Detection of New Vessels on the Optic Disc Using Retinal Photographs , 2011, IEEE Transactions on Medical Imaging.

[33]  B. Masters,et al.  Fractal analysis of the vascular tree in the human retina. , 2004, Annual review of biomedical engineering.

[34]  L. Aiello,et al.  Retinopathy in diabetes. , 2004, Diabetes care.