A Comprehensive Review of Early Detection of Diabetic Retinopathy from Digital Fundus Images
 |
International Journal of Computer Trends and Technology (IJCTT) | 
|
| © 2014 by IJCTT Journal | ||
| Volume-15 Number-1 |
||
| Year of Publication : 2014 | ||
| Authors : Padmalal S , Dr. Nelson Kennedy Babu C | ||
| DOI : 10.14445/22312803/IJCTT-V15P101 |
Padmalal S , Dr. Nelson Kennedy Babu C."A Comprehensive Review of Early Detection of Diabetic Retinopathy from Digital Fundus Images". International Journal of Computer Trends and Technology (IJCTT) V15(1):1-10, Sep 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
The effects of the eye abnormalities are mostly gradual in nature which shows the necessity for an accurate abnormality identification system. Abnormality in retina is one among them. Most of the ophthalmologists depend on the visual interpretation for the identification of the types of diseases. But, inaccurate diagnosis will change the course of treatment planning which leads to fatal results. Hence, there is a requirement for a bias free automated system which yields highly accurate results. In this paper, we are classifying normal and abnormal retina. . We first present an summary of diabetic retinopathy and its causes. Then, a literature review of the maximum current automatic detection of diabetic retinopathy techniques is offered. Explanation and restrictions of retina databases which are used to test the performance of these detection algorithms are given. Here we project a vital assessment of the current researches associated with the retinopathy detection process. In this paper, we present a wide review of major researches on disease detection process based on various features.
References
[1] Chisako Muramatsu, Yuji Hatanaka, Tatsuhiko Iwase, Takeshi Hara and Hiroshi Fujita," Automated selection of major arteries and veins for measurement of arteriolar-to-venular diameter ratio on retinal fundus images," Computerized Medical Imaging and Graphics, Vol. 35, pp.472–480, 2011.
[2] R. Vijayamadheswaran, Dr. M.Arthanari and M. Sivakumar," Detection of Diabetic Retinopathy using Radial Basics Function," International Journal of Innovative Technology and Creative Engineering, Vol.1 No.1, pp. 40-47, Jan 2011.
[3] Aliaa Abdel-Haleim Abdel-Razik Youssif, Atef Zaki Ghalwash, and Amr Ahmed Sabry Abdel-Rahman Ghoneim," Optic Disc Detection From Normalized Digital Fundus Images by Means of a Vessels’ Direction Matched Filter," IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 27, NO. 1, Jan 2008.
[4] Michael D. Abràmoff, Joseph M. Reinhardt, Stephen R. Russell, James C. Folk, Vinit B. Mahajan, Meindert Niemeijer and Gwénolé Quellec," Automated Early Detection of Diabetic Retinopathy," American Academy of Ophthalmology, pp. 1147-1154, 2010.
[5] I.B. Styles, A. Calcagni, E. Claridge, F. Orihuela-Espina, J.M. Gibson," Quantitative analysis of multi-spectral fundus images," Medical Image Analysis, Vol. 10, pp. 578–597, 2006.
[6] R S B Newsom, A Clover, M T J Costen, J Sadler, J Newton, A J Luvs and C R Canning," Effect of digital image compression on screening for diabetic retinopathy," British Journal of Ophthalmology, Vol. 85, pp. 799–802, 2001.
[7] Michael Goldbaum, Saied Moezzi, Adam Taylor, Shankar Chatterjee, Jeff Boyd, Edward Hunter, and Ramesh Jain," Automated diagnosis and image understanding with object extraction, object classification, and inferencing in retinal images," In Proc of the International Conference on Image Processing, Vol.3, Sep 1996.
[8] D. Usher, M. Dumsky , M. Himaga , T. H. Williamson , S. Nussey and J. Boyce," Automated detection of diabetic retinopathy in digital retinal images: a tool for diabetic retinopathy screening," journal of the British Diabetic Association, Vol. 21, No.1, pp. 84-90, 2004.
[9] Yuji Hatanaka, Toshiaki Nakagawa, Yoshinori Hayashi, Masakatsu Kakogawa, Akira Sawada, Kazuhide Kawase, Takeshi Hara and Hiroshi Fujita," Improvement of Automatic Hemorrhages Detection Methods using Brightness Correction on Fundus Images," In Proc of the international society of optics and photonics on medical imaging, Vol. 6915, 2008.
[10] Yuji Hatanaka, Toshiaki Nakagawa, Yoshinori Hayashi, Takeshi Hara and Hiroshi Fujita," Improvement of Automated Detection Method of Hemorrhages in Fundus Images," In Proc of the 30th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, pp. 5429 - 5432, Aug 2008.
[11] A.Osareh and B. Shadgar," Automatic Blood Vessel Segmentation in Color Images of Retina," Iranian Journal of Science & Technology, Vol. 33, No. 2, pp 191-206, 2009.
[12] Conor Heneghan , John Flynn , Michael O’Keefe and Mark Cahill," Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis," Medical Image Analysis, Vol. 6, No.4, pp. 407–429, 2002.
[13] P.N. Jebarani Sargunar and R.Sukanesh," Exudates Detection and Classification in Diabetic Retinopathy Images by Texture Segmentation Methods," International Journal of Recent Trends in Engineering, Vol 2, No. 4, pp. 148-150, Nov 2009.
[14] Daniela Matei and Radu Matei," Detection of Diabetic Symptoms in Retina Images Using Analog Algorithms," World Academy of Science, Engineering and Technology, Vol. 45, pp. 408-411, 2008.
[15] Arturo Aquino, Manuel Emilio Gegundez and Diego Marin," 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, 2009.
[16] Xinyu Xu, Baoxin Li, Automatic classification and detection of clinically-relevant images for diabetic retinopathy," society of optics and photonics, Vol.2 No.6, pp. 1-9, Jan 2008.
[17] Monireh Esnaashari, S. Amirhassan Monadjemi and Gholamali Naderian," A Content-based Retinal Image Retrieval Method for Diabetes Related Eye Diseases Diagnosis," International Journal of Research and Reviews in Computer Science (IJRRCS), Vol. 2, No. 6, pp. 1222-1227, Dec 2011.
[18] L. Giancardo, F. Meriaudeau, T.P. Karnowski, Y. Li, K.W. Tobin Jr. and E. Chaum," Automatic retina exudates segmentation without a manually labelled training set," International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1396 - 1400, Apr 2001.
[19] Ken Tobin and Edward Chaum," Automated screening aids diagnosis of diabetic eye disease," Biomedical Optics & Medical Imaging, Oct 2006.
[20] Luo Gang Opas Chutatape and Shankar M. Krishnan," Detection and Measurement of Retinal Vessels in Fundus Images Using Amplitude Modified Second-Order Gaussian Filter," IEEE Transactions on Biomedical Engineering, Vol. 49, No.2, pp. 168-172, Feb 2002.
[21] Giri Babu Kande, T.Satya Savithri and P.V.Subbaiah," Segmentation of Vessels in Fundus Images using Spatially Weighted Fuzzy c-Means Clustering Algorithm," International Journal of Computer Science and Network Security, Vol.7 No.12, pp. 102-109. Dec 2007.
[22] Meindert Niemeijer, Bram van Ginneken, Michael J. Cree, Atsushi Mizutani, Gwénolé Quellec, Clara I. Sánchez, Bob Zhang, Roberto Hornero , Mathieu Lamard, Chisako Muramatsu, Xiangqian Wu, Guy Cazuguel , Jane You, Agustín Mayo, Qin Li, Yuji Hatanaka, Béatrice Cochener,Christian Roux, Fakhri Karray, María García , Hiroshi Fujita and Michael D. Abràmoff," Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs," IEEE Transactions on Medical Imaging, Vol.29, No.1, pp. 185-195, Jan 2010.
[23] Balint Antal and Andras Hajdu," Improving Micro aneurysm Detection in Color Fundus images by using an optimal combination of preprocessing methods and candidate extractors," In Proc. of the 18th European Signal Processing Conference held in denmark, pp. 1224-1228, Aug 2010.
[24] Atsushi Mizutani, Chisako Muramatsu, Yuji Hatanaka, Shinsuke Suemori, Takeshi Hara and Hiroshi Fujita," Automated microaneurysm detection method based on double-ring filter in retinal fundus images," In Proc. of SPIE on Medical Imaging, Vol. 7260, 2008.
[25] Akara Sopharak, Bunyarit Uyyanonvara, Sarah Barman and Tom Williamson," Automatic Microaneurysm Detection from Non-dilated Diabetic Retinopathy Retinal Images," In Proc. of the World Congress on Engineering, Vol 2, Jul 2011.
[26] Apichat Suansilpong and Petch Rawdaree," Accuracy of Single-Field Nonmydriatic Digital Fundus Image in Screening for Diabetic Retinopathy," JJournal of Medical Association, Vol. 91, No.9, pp. 1397-1403, 2008.
[27] Akara Sopharak, Bunyarit Uyyanonvara and Sarah Barman," Automatic Microaneurysm Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Mathematical Morphology Methods," International Journal of Computer Science, Vol. 38, No. 3, Aug 2011.
[28] Nathan Silberman, Kristy Ahlrich, Rob Fergus and Lakshminarayanan Subramanian," Case for Automated Detection of Diabetic Retinopathy," In Proc of the Association for the Advancement of Artificial Intelligence, 2010.
[29] X. Merlin Sheeba and S. Vasanthi," An Efficient ELM Approach for Blood Vessel Segmentation in Retinal Images," International Journal of Man Machine Interface, Vol. 1, pp. 15-21, Dec 2011.
[30] Gopal Datt Joshi and Jayanthi Sivaswamy," DrishtiCare: A Telescreening Platform for Diabetic Retinopathy Powered with Fundus Image Analysis," Journal of Diabetes Science and Technology, Vol. 5, No. 1, pp. 1-9, Jan 2011.
[31] C.Jayakumari and R.Maruthi," Longitudinal time-series of color retinal Fundus Image for Diabetic Retinopathy," International Journal of Computer Applications,"Vol. 33, No.10, pp. 43-46, Nov 2011.
[32] Tu Ying, Xu Liang, Wei Wen-bin, Wang Shuang, Wang Ya-Xing and Jost B Jonas," Progression of diabetic retinopathy: the Beijing Eye Study," Chinese Medical Journal, Vol. 124, No. 22, pp. 3635-3640, 2011.
[33] V.Vijaya Kumari and N.SuriyaNarayanan," Diabetic Retinopathy-Early Detection Using Im-age Processing Techniques," International Journal on Computer Science and Engineering Vol. 02, No. 02, , 357-361, 2010.
[34] María García, María I. López, Daniel Álvarez and Roberto Hornero," Assessment of four neural network based classifiers to automatically detect red lesions in retinal images," Medical Engineering & Physics, Vol. 32, pp. 1085–1093, 2010.
[35] Clara I. Sánchez, Meindert Niemeijer, Alina V. Dumitrescu ,Maria S. A. Suttorp-Schulten, Michael D. Abràmoff and Bram van Ginneken," Evaluation of a Computer-Aided Diagnosis system for Diabetic Retinopathy screening on public data," In Proc. of the conference on Investigate Ophthalmology and Visual Science, Apr 2011.
[36] Priya. R and Aruna.P," Review of automated diagnosis of diabetic retinopathy using the support vector machine,"International Journal of Applied Engineering Research, Vol. 1, No. 4, pp. 844- 863, 2011.
[37] Desai Vidya, Ravi Shekhar, Siva Prabodh, N.V.S Chowdary, M.C. Das and M. JoJi Reddy," Oxidative Stress in Diabetic Retinopathy," Journal of Clinical and Diagnostic Research, Vol. 5, No. 5, pp. 994-997, Oct 2011.
[38] Arturo Aquino, Manuel Emilio Gegundez and Diego Marin," Automated Optic Disc Detection in Retinal Images of Patients with Diabetic Retinopathy and Risk of Macular Edema," International Journal of Biological and Life Sciences, Vol. 8, No. 2, pp. 87-92, 2012.
[39] Neera Singh and Ramesh Chandra Tripathi," Automated Early Detection of Diabetic Retinopathy Using Image Analysis Techniques," International Journal of Computer Applications," Vol. 8, No.2, pp. 18-23, Oct 2010.
[40] Hussain F. Jaafar, Asoke K. Nandi and Waleed Al-Nuaimy," Automated Detection of Exudates in Retinal Images Using a Split and Merge Algorithm," In Proc. of the European Conference on Signal Processing, Aug 2010.
Keywords
Gabor filtering, Adaptive histogram equalization, optic disk measurement, RGB segmentation, OCT, Skeletonization, Vein diameter measurement.