Fractal Matrix and Morphological Analysis of Retinal Vascular Regions

In this scientific paper there is presented a new methodology based on morphological fractal analysis of the retinal vascularisation regions of the eye in order to detect the differences between normal retinal regions and the ones affected by glaucoma and/or diabetic retinopathy. There has been employed differentiation techniques based on fractal dimension computation and network complexity, such as the number of fractal branching points, end points and vessel segments. The necessary information for the statistical evaluations has been extracted from the fractal matrix associated to the analyzed images. The parameters variations in certain retinal regions are correlated with a specific disease, as it can be observed from the results.

[1]  K. L. Uahabi,et al.  Applications of fractals in medicine , 2015 .

[2]  S. Miller.  ANGIOGRAPHY , 1951, The British journal of ophthalmology.

[3]  Christian Vasseur,et al.  Fractal Dimension for the Analysis of Vascular Diseases on X-Ray Angiography , 2015, 2015 20th International Conference on Control Systems and Computer Science.

[4]  Andreas K. Maier,et al.  Robust Vessel Segmentation in Fundus Images , 2013, Int. J. Biomed. Imaging.

[6]  Leonard M. Sander,et al.  Fractal dimensions of the Q-state Potts model for complete and external hulls , 2009, 1001.0055.

[7]  Sebastian Stach,et al.  Analysis of normal human retinal vascular network architecture using multifractal geometry. , 2017, International journal of ophthalmology.

[8]  C. Sparrow.  The Fractal Geometry of Nature , 1984 .

[9]  A. Gupta,et al.  Beyond Linear Methods of Data Analysis: Time Series Analysis and Its Applications in Renal Research , 2013, Nephron Physiology.

[10]  E. Weibel,et al.  Fractals in Biology and Medicine , 1994 .

[11]  R. Nogueira,et al.  Fractal, multifractal and lacunarity analysis applied in retinal regionsof diabetic patients with and without non-proliferative diabetic retinopathy , 2016 .

[12]  S. Blacher,et al.  Fractal Quantification of the Microvasculature Heterogeneity in Cutaneous Melanoma , 1999, Dermatology.

[13]  Temitope Mapayi,et al.  AUTOMATIC RETINAL VESSEL DETECTION AND TORTUOSITY MEASUREMENT , 2016 .

[14]  U. Frydkjaer-Olsen,et al.  Retinal Vascular Fractals Correlate With Early Neurodegeneration in Patients With Type 2 Diabetes Mellitus. , 2015, Investigative ophthalmology & visual science.

[15]  T. Ruzicka,et al.  mHealth App for Risk Assessment of Pigmented and Nonpigmented Skin Lesions-A Study on Sensitivity and Specificity in Detecting Malignancy. , 2017, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.