International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 7, No. 7, 8 Jun. 2015
Cover page and Table of Contents: PDF (size: 646KB)
A Novel Approach to Diagnose Diabetic Retinopathy
Full Text (PDF, 646KB), PP.9-16
Views: 0 Downloads: 0
Author(s)
Dharmanna Lamani
1,*
T. C. Manjunath
2
Mahesh M
3
Y S Nijagunaraya
4
Index Terms
Diabetic Retinopathy, Fractal Dimension, Entropy, Gray Level Co-occurrence Matrix
Abstract
Early identification of diabetic retinopathy is highly beneficial for preventing the progression of disease. Appearance of blood vessels & retinal surface is a good ophthalmological sign of diabetic retinopathy in fundus images. In this paper, a novel method involving two approaches has been proposed for diagnosis of diabetic retinopathy. The first approach deals with estimation of fractal dimension of lesions by applying power spectral fractal dimension algorithms. For healthy retinas, fractal dimensions are found to be in the range of 2.00 to 2.069, whereas for retinas with diabetic retinopathy, fractal dimensions exceed upper limit. In the second approach, Gray Level Co-occurrence Matrix method is used to analyze the extracted regions from healthy and diabetes affected fundus retinal images. Texture features such as entropy & contrast are computed for healthy and unhealthy regions. These texture features are compared with fractal dimensions. The authors observed positive correlation between entropy and fractal dimensions, whereas negative correlation with contrast and fractal dimensions. Detailed implementations of the proposed work are presented.
Cite This Paper
Dharmanna Lamani, T C Manjunath, Mahesh M, Y S Nijagunaraya,"A Novel Approach to Diagnose Diabetic Retinopathy", IJIGSP, vol.7, no.7, pp.9-16, 2015. DOI: 10.5815/ijigsp.2015.07.02
Reference
[1]A.C.B. Kunicki, A.J. Oliveira, M.B.M. Mendonça,C.T.F. Barbosa and R.A. Nogueira, "Can the fractal dimension be applied for the early diagnosis of non-proliferative diabetic retinopathy?", Brazilian Journal of Medical and Biological Research (2009) 42: 930-934.
[2]Shueh wen lim, ning cheung, jie j. Wang, kim c. Donaghue, gerald liew, f.m. amirul islam, alicia j. Jenkins, tien y. Wong, "Retinal Vascular Fractal Dimension and Risk of Early Diabetic Retinopathy", Diabetes Care, Volume 32, Number 11, November 2009.
[3]Nazneen Akhter, Yogesh Rajput, Sumegh Tharewal, K. V. Kale, Ramesh Manza, "Fractals For Complexity Analysis Of Diabetic Retinopathy In Retinal Vasculature Images", International Journal of Research in Engineering and Technology Volume: 03 Issue: 03 | Mar-2014.
[4]Dharmanna Lamani, Dr. T. C. Manjunath, Dr. U P Kulkarni, "Automated Detection of Neovascular Glaucoma through Fractal Dimension Method", International Journal of Computer Science and Information Technologies, Vol. 5 (4), 2014.
[5]Myra Poon, Maria E. Craig, Harleen Kaur, Janine Cusumano, Muhammad Bayu Sasongko, Tien YinWong and Kim C. Donaghue, "Vitamin D Deficiency Is Not Associated with Changes in Retinal Geometric Parameters in Young People with Type 1 Diabetes", Hindawi Publishing Corporation Journal of Diabetes Research Volume 2013, Article ID 280691.
[6]Gerald Liew, Jie Jin Wang, Paul Mitchell, Tien Y. Wong, "Retinal Vascular Imaging: A New Tool in Microvascular Disease Research", Circ Cardiovasc Imaging September 2008.
[7]Behzad Aliahmad, Dinesh Kant Kumar, Hao Hao, Premith Unnikrishnan, Mohd Zulfaezal Che Azemin, Ryo Kawasaki, PaulMitchell, "Zone Specific Fractal Dimension of Retinal Images as Predictor of Stroke Incidence", Hindawi Publishing Corporation, The Scientific World Journal, Volume 2014, Article ID 467462.
[8]Dr.Chandrashekar. M. Patil, "An Approach for the Detection of Vascular Abnormalities in Diabetic Retinopathy", International Journal of Data Mining Techniques and Applications Vol: 02, December 2013, Pages: 246-250.
[9]Albert Daxer, "Characterisation of Neovascularisation process in diabetic retinopathy by means of fractal geometry: diagnostic implications", Graefe's Archieve for Clinical and Experimental Opthomology, Springer-Verlag, 1993.
[10]Ravishankar S, Jain A, Mittal A, "Automated feature extraction for early detection of diabetic retinopathy in fundus images", IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2009.
[11]Gábor Márk Somfai, Erika Tátrai, Lenke Laurik, Boglárka E Varga, Vera Ölvedy, William E Smiddy, Robert Tchitnga, Anikó Somogyi and Delia Cabrera DeBuc, "BMC Bioinformatics 2014, 15:295",
[12]Manoj Kumar Rathore, Mayank Kumar, Surendra yadav, Awanish Mishra, "Estimation of Fractal Dimension of Digital Images", International Journal of Engineering and Technical Research (IJETR) ISSN: 2321-0869, Volume-2, Issue-9, September 2014.
[13]T. Pant, "Effect of Noise in Estimation of Fractal Dimension of Digital Images", International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.6, No.5 (2013), pp.101-116.
[14]P. Pentland, "Fractal-based description of natural scenes", IEEE Trans. Pattern Anal. Mach. Intell., PAMI-6, (1984), pp. 661-674.
[15]R.Radha and Bijee Lakshman, "Retinal Image Analysis Using Morphological Process and Clustering Technique", Signal & Image Processing: An International Journal (SIPIJ) Vol.4, No.6, December 2013.
[16]Selvathi D, N.B.Prakash, Neethi Balagopal, "Automated Detection of Diabetic Retinopathy for Early Diagnosis using Feature Extraction and Support Vector Machine ", International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, Volume 2, Issue 11, November 2012.
[17]P. Shanmugavadivu, V. Sivakumar, "Fractal Dimension based Textural Analysis Digital Images", Procedia Engineering 38 (2012) 2981 – 2986.
[18]Malhar Kale, Ferry Butar Butar, "Fractal Analysisof Time Series and Distribution Properties of Hurst Exponet", Journal of Mathematical Science and Mathematics Education, Vol. 5, Issue 1, PP. 9-19.
[19]Misson G P, Landini G, Murray P I, Fractals and Ophthalmology, Lancet 339:872.