Research Journal of Pharmacy and Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Digital Diagnosis of Diabetic Retinopathy using Fundus Images


Affiliations
1 Instrumentation Engineering Department, Karunya Institute of Technology and Sciences, Coimbatore, India
     

   Subscribe/Renew Journal


Diabetic retinopathy is a condition where the retina of the eye is affected due to diabetes. It eventually leads to blindness. It is a systemic disease which is an ocular manifestation of diabetes. It affects almost 80 percent of people with prolonged and acute diabetes for 20 years or more. Inspite of these intimidating statistics, advanced researchers propose that monitoring of eyes enables earlier detection of symptoms that can help reduce blinding of eyes by more than 90%. United States, records 12% of all new cases of blindness due to diabetic retinopathy. It is also the leading cause of blindness for people aged 20 to 64 years. Therefore serious efforts are being taken by engineers to develop efficient ways of detecting this diabetic retinopathy through image processing of fundus images. Automated Blood Vessel Extraction algorithms save time, protects patient’s vision and reduces unwanted medical costly treatments. This paper analyzes on the image of human eye captured from the fundus camera and proposes a methodology for detection of Diabetic Retinopathy using Image Enhancement.

Keywords

Diabetic Retinopathy, Micro Aneurysms, Support Vector Machine, Retinal Fundus.
Subscription Login to verify subscription
User
Notifications
Font Size


  • Carla Agurto, Honggang Yu,Victor Murray “Detection of Hard Exudates and Red Lesions in the Macula Using a Multiscale Approach” IEEE Southwest Symposium on Image Analysis and Interpretation 2012.

  • Ravi Shankar, Jain, Mittal “Automated Feature Extraction for Early Detection of Diabetic Retinopathy in Fundus Images” IEEE Conference on Computer Vision and Pattern Recognition 2009.

  • Miri, M.S, Mahloojifar A “A comparison study to evaluate retinal image enhancement techniques” IEEE International Conference on Signal and Image Processing Applications 2009.

  • Di Wu, Ming Zhang, Jyh-Charn Liu, and Wendall Bauman “On the Adaptive Detection of Blood Vessels in Retinal Images” IEEE Trans Biomed Engineering 2006.

  • Feman, S.S, Leonard-Martin T.C, Andrews J.S “A quantitative system to evaluate diabetic retinopathy from fundus photographs” Invest Ophthalmol Vis Sci, 1995 Jan; 36(1):174-81.

  • Gardner, G.G, Keating D, Williamson, T.H, Elliot A.T “Automatic Detection of Diabetic Retinopathy using an Artificial Neural Network: a Screening Tool” Br. J. Ophthalmol. 1996, 80,940-944.

  • Raju Maher, Dr.Mukta Dhopeshwarkar “Automated Detection of Non-proliferative Diabetes RetinopathyUsing Fundus Images” International Journal of Advanced Research in Computer Science and Software Engineering Volume 5, Issue 3, March 2015.

  • Bresnick GH, Mukamel DB, Dickinson JC, Cole DR “A screening approach to the surveillance of patients with diabetes for the presence of vision-threatening retinopathy” Ophthalmology. 2000; 107:19–24.

  • Kinyoun JL, Martin DC, Fujimoto WY, Leonetti DL “Ophthalmoscopy versus fundus photographs for detecting and grading diabetic retinopathy” Invest Ophthalmol Vis Sci. 1992;33:1888–93.

  • Raju Sahebrao Maher, Sangramsing N. Kayte, Sandip T. Meldhe, Mukta Dhopeshwarkar, “Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine” International Journal of Computer Applications (0975 – 8887)Volume 125 – No.15, September 2015.

  • A. Osareh, M. Mirmehdi, B. Thomas and R. Markham “Automated identification of diabetic retinal exudates in digital colour images”, Ophthalmol, vol. 87, pp. 1220-23, 2003.

  • Walter, T. Klein, J. Massin, P. Erginay, “A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina‖” IEEE Transactions on Medical Imaging Volume: 21, Issue: 10, Oct. 2002.

  • E. N. Marieb “Human Anatomy and Physiology” Pearson Education, 6th Edition ed., 2006

  • Hanieh Poostchi “Diabetic Retinopathy Dark lesion detection: Preprocessing phase‖” 1st Int. Conf. on Computer and Knowledge Engineering, October 2011, pp. 177- 181.

  • Akara Sopharak, Bunyarit Uyyanonvara and Sarah Barman,” Automatic Exudate Detection from Non- dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering” Sensors 2009, 9, pages 2148-2161.

  • A. D. Fleming “The role of Exudates and Hemorrhage in automatic grading of Diabetic Retinopathy ‖” Br. J. Ophthalmol.,vol. 94, pp. 706 – 711, 2010.

  • Arturo Aquino, Manuel Emilio Gegundez, Diego Martin (2009), “Automated optic disc detection in retinal images of patients with diabetic retinopathy and risk of macular edema” World Academy of Science, Engineering and technology, Vol. 60, pp.85-90.

  • Balanco M., Penedo M.G., Barreira N.,Penas M., Carreira M.J “Localisation and extraction of the optic disc using the fuzzy circular hough transform” Springer Lecture Notes in Computer Science, pp. 712-721, 2006

  • Panfang Hua, Qi Song, Milan Sonka, Eric A. Hoffman and Joseph M. Reinhardt “Segmentation of pathological and diseased lung tissue in CT images using a graph-search algorithm” IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011


Abstract Views: 148

PDF Views: 0




  • Digital Diagnosis of Diabetic Retinopathy using Fundus Images

Abstract Views: 148  |  PDF Views: 0

Authors

P. Vijay Daniel
Instrumentation Engineering Department, Karunya Institute of Technology and Sciences, Coimbatore, India
D. Pamela
Instrumentation Engineering Department, Karunya Institute of Technology and Sciences, Coimbatore, India
P. Kingston Stanley
Instrumentation Engineering Department, Karunya Institute of Technology and Sciences, Coimbatore, India
J. Samson Issac
Instrumentation Engineering Department, Karunya Institute of Technology and Sciences, Coimbatore, India

Abstract


Diabetic retinopathy is a condition where the retina of the eye is affected due to diabetes. It eventually leads to blindness. It is a systemic disease which is an ocular manifestation of diabetes. It affects almost 80 percent of people with prolonged and acute diabetes for 20 years or more. Inspite of these intimidating statistics, advanced researchers propose that monitoring of eyes enables earlier detection of symptoms that can help reduce blinding of eyes by more than 90%. United States, records 12% of all new cases of blindness due to diabetic retinopathy. It is also the leading cause of blindness for people aged 20 to 64 years. Therefore serious efforts are being taken by engineers to develop efficient ways of detecting this diabetic retinopathy through image processing of fundus images. Automated Blood Vessel Extraction algorithms save time, protects patient’s vision and reduces unwanted medical costly treatments. This paper analyzes on the image of human eye captured from the fundus camera and proposes a methodology for detection of Diabetic Retinopathy using Image Enhancement.

Keywords


Diabetic Retinopathy, Micro Aneurysms, Support Vector Machine, Retinal Fundus.

References