Application of different imaging modalities for diagnosis of Diabetic Macular Edema: A review

Diabetic Macular Edema (DME) is caused by accumulation of extracellular fluid from hyperpermeable capillaries within the macula. DME is one of the leading causes of blindness among Diabetes Mellitus (DM) patients. Early detection followed by laser photocoagulation can save the visual loss. This review discusses various imaging modalities viz. biomicroscopy, Fluorescein Angiography (FA), Optical Coherence Tomography (OCT) and colour fundus photographs used for diagnosis of DME. Various automated DME grading systems using retinal fundus images, associated retinal image processing techniques for fovea, exudate detection and segmentation are presented. We have also compared various imaging modalities and automated screening methods used for DME grading. The reviewed literature indicates that FA and OCT identify DME related changes accurately. FA is an invasive method, which uses fluorescein dye, and OCT is an expensive imaging method compared to fundus photographs. Moreover, using fundus images DME can be identified and automated. DME grading algorithms can be implemented for telescreening. Hence, fundus imaging based DME grading is more suitable and affordable method compared to biomicroscopy, FA, and OCT modalities.

[1]  Frans Coenen,et al.  Data mining techniques for the screening of age-related macular degeneration , 2012, Knowl. Based Syst..

[2]  Jasjit S. Suri,et al.  Computer-Based Identification of Diabetic Maculopathy Stages Using Fundus Images , 2011 .

[3]  Nazimul Hussain,et al.  Volcano like pattern in optical coherence tomography in chronic diabetic macular edema. , 2014, Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological Society.

[4]  Asoke K. Nandi,et al.  Automated localisation of the optic disc and fovea to assist diabetic retinopathy screenings , 2013, 21st European Signal Processing Conference (EUSIPCO 2013).

[5]  Christian Simader,et al.  A systematic correlation of angiography and high-resolution optical coherence tomography in diabetic macular edema. , 2009, Ophthalmology.

[6]  M. Sonka,et al.  Retinal Imaging and Image Analysis , 2010, IEEE Reviews in Biomedical Engineering.

[7]  M. Goldbaum,et al.  Detection of blood vessels in retinal images using two-dimensional matched filters. , 1989, IEEE transactions on medical imaging.

[8]  D. Abraham Chandy,et al.  Content-based retinal image retrieval using dual-tree complex wavelet transform , 2013, 2013 International Conference on Signal Processing , Image Processing & Pattern Recognition.

[9]  M. Usman Akram,et al.  Automated system for macula detection in digital retinal images , 2011, 2011 International Conference on Information and Communication Technologies.

[10]  Pascale Massin,et al.  A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina , 2002, IEEE Transactions on Medical Imaging.

[11]  U. Rajendra Acharya,et al.  Ensemble selection for feature-based classification of diabetic maculopathy images , 2013, Comput. Biol. Medicine.

[12]  S. Kishi,et al.  Patterns of diabetic macular edema with optical coherence tomography. , 1999, American journal of ophthalmology.

[13]  Gabriel Coscas,et al.  Steroids and Macular Edema from Retinal Vein Occlusion , 2011, European journal of ophthalmology.

[14]  J. Olson,et al.  Automatic detection of retinal anatomy to assist diabetic retinopathy screening , 2007, Physics in medicine and biology.

[15]  Ahmed S. Fahmy,et al.  Content based image retrieval of diabetic macular edema images , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[16]  Massimo Porta,et al.  Medical management for the prevention and treatment of diabetic macular edema. , 2013, Survey of ophthalmology.

[17]  Seiyo Harino,et al.  Relationship of macular microcirculation and retinal thickness with visual acuity in diabetic macular edema. , 2007, Ophthalmology.

[18]  U. Acharya,et al.  Automatic identification of diabetic maculopathy stages using fundus images , 2009, Journal of medical engineering & technology.

[19]  U. Rajendra Acharya,et al.  Evolutionary algorithm based classifier parameter tuning for automatic diabetic retinopathy grading: A hybrid feature extraction approach , 2013, Knowl. Based Syst..

[20]  Charles V. Stewart,et al.  Robust detection and classification of longitudinal changes in color retinal fundus images for monitoring diabetic retinopathy , 2006, IEEE Transactions on Biomedical Engineering.

[21]  James G Fujimoto,et al.  CHOROIDAL THICKNESS IN PATIENTS WITH DIABETIC RETINOPATHY ANALYZED BY SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHY , 2011, Retina.

[22]  Catherine Egan,et al.  SDOCT Imaging to Identify Macular Pathology in Patients Diagnosed with Diabetic Maculopathy by a Digital Photographic Retinal Screening Programme , 2011, PloS one.

[23]  Andrew Hunter,et al.  Automated diagnosis of referable maculopathy in diabetic retinopathy screening , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[24]  Jennifer I. Lim,et al.  Relationship between optical coherence tomography-measured central retinal thickness and visual acuity in diabetic macular edema. , 2007, Ophthalmology.

[25]  Jayanthi Sivaswamy,et al.  Appearance-based object detection in colour retinal images , 2008, 2008 15th IEEE International Conference on Image Processing.

[26]  U. Rajendra Acharya,et al.  Data mining technique for automated diagnosis of glaucoma using higher order spectra and wavelet energy features , 2012, Knowl. Based Syst..

[27]  U. Rajendra Acharya,et al.  Application of higher-order spectra for automated grading of diabetic maculopathy , 2015, Medical & Biological Engineering & Computing.

[28]  S. Wild,et al.  Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. , 2004, Diabetes care.

[29]  Mong-Li Lee,et al.  The role of domain knowledge in the detection of retinal hard exudates , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[30]  S. Dandapat,et al.  Automatic grading of macular degeneration from color fundus images , 2012, 2012 World Congress on Information and Communication Technologies.

[31]  N. Bressler,et al.  Ketorolac treatment of pseudophakic cystoid macular edema identified more than 24 months after cataract extraction. , 1999, Ophthalmology.

[32]  Bram van Ginneken,et al.  Segmentation of the Optic Disc, Macula and Vascular Arch in Fundus Photographs , 2007, IEEE Transactions on Medical Imaging.

[33]  Kenneth W. Tobin,et al.  Exudate-based diabetic macular edema detection in fundus images using publicly available datasets , 2012, Medical Image Anal..

[34]  Luís Pinto,et al.  Monte Carlo simulation of diabetic macular edema changes on optical coherence tomography data , 2014, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

[35]  D. Kangave,et al.  The correlation between optical coherence tomographic features and severity of retinopathy, macular thickness and visual acuity in diabetic macular edema , 2006, International Ophthalmology.

[36]  C. Sinthanayothin,et al.  Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images , 1999, The British journal of ophthalmology.

[37]  Sang Yeop Lee,et al.  Foveal ganglion cell layer damage in ischemic diabetic maculopathy: correlation of optical coherence tomographic and anatomic changes. , 2009, Ophthalmology.

[38]  Adarsh Punnolil,et al.  A novel approach for diagnosis and severity grading of diabetic maculopathy , 2013, 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[39]  W. Benson,et al.  HIGH-RESOLUTION STEREOSCOPIC DIGITAL FUNDUS PHOTOGRAPHY VERSUS CONTACT LENS BIOMICROSCOPY FOR THE DETECTION OF CLINICALLY SIGNIFICANT MACULAR EDEMA , 2002 .

[40]  Bartosz L. Sikorski,et al.  The Diagnostic Function of OCT in Diabetic Maculopathy , 2013, Mediators of inflammation.

[41]  Andrew Hunter,et al.  Using shape entropy as a feature to lesion boundary segmentation with level sets , 2009 .

[42]  B. Thomas,et al.  Automated identification of diabetic retinal exudates in digital colour images , 2003, The British journal of ophthalmology.

[43]  U. Rajendra Acharya,et al.  Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method , 2015, Knowl. Based Syst..

[44]  Asoke K. Nandi,et al.  Automated localisation of optic disk and fovea in retinal fundus images , 2008, 2008 16th European Signal Processing Conference.

[45]  Masanori Hayashi,et al.  Morphological and functional analyses of diabetic macular edema by optical coherence tomography and multifocal electroretinograms , 2001, Graefe's Archive for Clinical and Experimental Ophthalmology.

[46]  Salah Bourennane,et al.  Detection of the foveal avascular zone on retinal angiograms using Markov random fields , 2010, Digit. Signal Process..

[47]  Christos Haritoglou,et al.  Topography of diabetic macular oedema compared with fluorescein angiography. , 2006, Acta ophthalmologica Scandinavica.

[48]  Afef Maalej,et al.  Optical Coherence Tomography for Diabetic Macular Edema: Early Diagnosis, Classification and Quantitative Assessment , 2011 .

[49]  Jacob Scharcanski,et al.  Fovea center detection based on the retina anatomy and mathematical morphology , 2011, Comput. Methods Programs Biomed..

[50]  J. Olson,et al.  The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy , 2009, British Journal of Ophthalmology.

[51]  V. K. Govindan,et al.  Automatic Grading of Severity of Diabetic Macular Edema Using Color Fundus Images , 2013, 2013 Third International Conference on Advances in Computing and Communications.

[52]  Ali Erginay,et al.  Optical coherence tomography features during the evolution of serous retinal detachment in patients with diabetic macular edema. , 2008, American journal of ophthalmology.

[53]  J. Olson,et al.  Automated grading for diabetic retinopathy: a large-scale audit using arbitration by clinical experts , 2010, British Journal of Ophthalmology.

[55]  W. Hsu,et al.  Quantitative assessment of retinal thickness in diabetic patients with and without clinically significant macular edema using optical coherence tomography. , 2001, Acta ophthalmologica Scandinavica.

[56]  Roberto Hornero,et al.  Retinal image analysis based on mixture models to detect hard exudates , 2009, Medical Image Anal..

[57]  W. Goebel,et al.  RETINAL THICKNESS IN DIABETIC RETINOPATHY: A Study Using Optical Coherence Tomography (OCT) , 2002, Retina.

[58]  Thomas Martini Jørgensen,et al.  Enhanced optical coherence patterns of diabetic macular oedema and their correlation with the pathophysiology. , 2008, Acta ophthalmologica Scandinavica.

[59]  J. G. Flanagan,et al.  Agreement of the Heidelberg Retina Tomograph II Macula Edema Module with Contact Lens Stereo Fundus Biomicroscopy in Early Diabetic Maculopathy. , 2004 .

[60]  Anam Tariq,et al.  A Gaussian Mixture Model Based System for Detection of Macula in Fundus Images , 2012, ICONIP.

[61]  N. Bressler,et al.  Detection of diabetic macular edema: Nidek 3Dx stereophotography compared with fundus biomicroscopy. , 1996, American journal of ophthalmology.

[62]  Mohamed Ibrahim,et al.  Quantitative assessment of Diabetic Macular Edema using fluorescein leakage maps , 2012, 2012 19th IEEE International Conference on Image Processing.

[63]  Roberto Hornero,et al.  A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis. , 2008, Medical engineering & physics.

[64]  Ali Erginay,et al.  Optical coherence tomography assessment of the vitreoretinal relationship in diabetic macular edema. , 2005, American journal of ophthalmology.

[65]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[66]  Sumeet Dua,et al.  Computational Analysis of the Human Eye with Applications , 2011 .

[67]  Hamzah Arof,et al.  Exudates segmentation using inverse surface adaptive thresholding , 2012 .

[68]  Huiqi Li,et al.  Automated feature extraction in color retinal images by a model based approach , 2004, IEEE Transactions on Biomedical Engineering.

[69]  Kenneth W. Tobin,et al.  Detection of Anatomic Structures in Human Retinal Imagery , 2007, IEEE Transactions on Medical Imaging.

[70]  J. Olson,et al.  Automated detection of exudates for diabetic retinopathy screening , 2007, Physics in medicine and biology.

[71]  Rui Bernardes Optical coherence tomography: Health information embedded on OCT signal statistics , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[72]  Christoph Hirneiss,et al.  Tele-screening for diabetic retinopathy with the retinal thickness analyzer. , 2003, Diabetes care.

[73]  Maciej Wojtkowski,et al.  Retinal assessment using optical coherence tomography , 2006, Progress in Retinal and Eye Research.

[74]  M. Shahidi,et al.  Clinical assessment of the macula by retinal topography and thickness mapping. , 1997, American journal of ophthalmology.

[75]  Treatment techniques and clinical guidelines for photocoagulation of diabetic macular edema. Early Treatment Diabetic Retinopathy Study Report Number 2. Early Treatment Diabetic Retinopathy Study Research Group. , 1987, Ophthalmology.

[76]  R. Bernardes,et al.  Central retinal thickness measured with HD-OCT shows a weak correlation with visual acuity in eyes with CSME , 2010, British Journal of Ophthalmology.

[77]  Sharon D. Solomon,et al.  Detection of diabetic foveal edema: contact lens biomicroscopy compared with optical coherence tomography. , 2004, Archives of ophthalmology.

[78]  Bálint Antal,et al.  An ensemble-based system for automatic screening of diabetic retinopathy , 2014, Knowl. Based Syst..

[79]  J. Caprioli,et al.  Optical coherence tomography to detect and manage retinal disease and glaucoma. , 2004, American journal of ophthalmology.

[80]  Gilda Cennamo,et al.  Evaluation of ischemic diabetic maculopathy with Fourier-domain optical coherence tomography and microperimetry. , 2015, Canadian journal of ophthalmology. Journal canadien d'ophtalmologie.

[81]  M. Usman Akram,et al.  Retinal image analysis for diagnosis of macular edema using digital fundus images , 2013, 2013 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT).

[82]  P. C. Siddalingaswamy,et al.  Automatic grading of diabetic maculopathy severity levels , 2010, 2010 International Conference on Systems in Medicine and Biology.

[83]  H. Pourreza,et al.  Localization of hard exudates in retinal fundus image by mathematical morphology operations , 2012, 2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE).

[84]  Jayanthi Sivaswamy,et al.  Automatic assessment of macular edema from color retinal images , 2012, IEEE Transactions on Medical Imaging.

[85]  Bram van Ginneken,et al.  Fast detection of the optic disc and fovea in color fundus photographs , 2009, Medical Image Anal..

[86]  S. Balasubramanian,et al.  Automatic Detection of Anatomical Structures in Digital Fundus Retinal Images , 2007, MVA.

[87]  L. Aiello,et al.  Detection of diabetic macular edema. Ophthalmoscopy versus photography--Early Treatment Diabetic Retinopathy Study Report Number 5. The ETDRS Research Group. , 1989, Ophthalmology.

[88]  Michael Larsen,et al.  Correlation between intraretinal changes in diabetic macular oedema seen in fluorescein angiography and optical coherence tomography , 2008, Acta ophthalmologica.

[89]  Alexander R de Leon,et al.  High-resolution stereoscopic digital fundus photography versus contact lens biomicroscopy for the detection of clinically significant macular edema. , 2002, Ophthalmology.

[90]  Ali Erginay,et al.  Characterization of macular edema from various etiologies by optical coherence tomography. , 2005, American journal of ophthalmology.

[91]  Marios S. Pattichis,et al.  Multiscale AM-FM Methods for Diabetic Retinopathy Lesion Detection , 2010, IEEE Transactions on Medical Imaging.

[92]  M. Usman Akram,et al.  Automated Detection and Grading of Diabetic Maculopathy in Digital Retinal Images , 2013, Journal of Digital Imaging.

[93]  Gabriel Coscas,et al.  Macular edema in central retinal vein occlusion: correlation between optical coherence tomography, angiography and visual acuity , 2012, International Ophthalmology.

[94]  Marcus-Matthias Gellrich,et al.  The fundus slit lamp , 2015, SpringerPlus.

[95]  Lalit Verma,et al.  Diabetic retinopathy: time for action. No complacency please! , 2002, Bulletin of the World Health Organization.

[96]  B. Zinman,et al.  Diabetic retinopathy and diabetic macular edema: pathophysiology, screening, and novel therapies. , 2003, Diabetes care.

[97]  R. Hornero,et al.  Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy , 2003, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[98]  Kenneth W. Tobin,et al.  Automatic retina exudates segmentation without a manually labelled training set , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[99]  J. Duker,et al.  Imaging of macular diseases with optical coherence tomography. , 1995, Ophthalmology.

[100]  Sungbin Lim,et al.  Automatic classification of diabetic macular edema in digital fundus images , 2011, 2011 IEEE Colloquium on Humanities, Science and Engineering.

[101]  Peter K Kaiser,et al.  Optical coherence tomographic patterns of diabetic macular edema. , 2006, American journal of ophthalmology.

[102]  Srinivas R Sadda,et al.  Predicting visual outcomes for macular disease using optical coherence tomography. , 2011, Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological Society.

[103]  Keshab K. Parhi,et al.  Automated localization of cysts in diabetic macular edema using optical coherence tomography images , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[104]  Jacob Scharcanski,et al.  A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images , 2010, Comput. Medical Imaging Graph..

[105]  Ran Zeimer,et al.  Comparison between retinal thickness analyzer and optical coherence tomography for assessment of foveal thickness in eyes with macular disease , 2003 .

[106]  Matthias Bolz,et al.  Optical coherence tomographic hyperreflective foci: a morphologic sign of lipid extravasation in diabetic macular edema. , 2009, Ophthalmology.

[107]  C. Sinthanayothin,et al.  Automated detection of diabetic retinopathy on digital fundus images , 2002, Diabetic medicine : a journal of the British Diabetic Association.

[108]  Muhammad Younus Javed,et al.  An Automated System for the Grading of Diabetic Maculopathy in Fundus Images , 2012, ICONIP.

[109]  Samarendra Dandapat,et al.  Analysis of maculopathy in color fundus images , 2014, 2014 Annual IEEE India Conference (INDICON).

[110]  Ahmed S. Fahmy,et al.  Segmentation of Diabetic Macular Edema in fluorescein angiograms , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[111]  Dawn A Sim,et al.  Quantitative analysis of diabetic macular ischemia using optical coherence tomography. , 2014, Investigative ophthalmology & visual science.

[112]  G. Bresnick,et al.  DIABETIC MACULAR EDEMA: A REVIEW , 1986 .

[113]  Hossein Rabbani,et al.  Analysis of foveal avascular zone for grading of diabetic retinopathy severity based on curvelet transform , 2012, Graefe's Archive for Clinical and Experimental Ophthalmology.

[114]  Kevin Noronha,et al.  Classification of diabetes maculopathy images using data-adaptive neuro-fuzzy inference classifier , 2015, Medical & Biological Engineering & Computing.

[115]  Matthias Bolz,et al.  Detection and analysis of hard exudates by polarization-sensitive optical coherence tomography in patients with diabetic maculopathy. , 2014, Investigative ophthalmology & visual science.

[116]  Alireza Osareh,et al.  A Computational-Intelligence-Based Approach for Detection of Exudates in Diabetic Retinopathy Images , 2009, IEEE Transactions on Information Technology in Biomedicine.

[117]  M. Obermaier,et al.  A telemedical approach to the screening of diabetic retinopathy: digital fundus photography. , 2000, Diabetes care.

[118]  Bunyarit Uyyanonvara,et al.  Automatic exudate detection for diabetic retinopathy screening , 2009 .

[119]  S. Gibran,et al.  Optical coherence tomographic pattern may predict visual outcome after intravitreal triamcinolone for diabetic macular edema. , 2007, Ophthalmology.

[120]  Richard B Rosen,et al.  Correlation between spectral domain optical coherence tomography findings and fluorescein angiography patterns in diabetic macular edema. , 2009, Ophthalmology.

[121]  L. Aiello,et al.  Stereo nonmydriatic digital-video color retinal imaging compared with Early Treatment Diabetic Retinopathy Study seven standard field 35-mm stereo color photos for determining level of diabetic retinopathy. , 2001, Ophthalmology.

[122]  Marios S. Pattichis,et al.  A Multiscale Optimization Approach to Detect Exudates in the Macula , 2014, IEEE Journal of Biomedical and Health Informatics.

[123]  Joel S Schuman,et al.  Automated detection of clinically significant macular edema by grid scanning optical coherence tomography. , 2006, Ophthalmology.

[124]  B. van Ginneken,et al.  Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis. , 2007, Investigative ophthalmology & visual science.

[125]  Uğur Şevik,et al.  Automatic segmentation of age-related macular degeneration in retinal fundus images , 2008, Comput. Biol. Medicine.

[126]  Miguel J Maldonado,et al.  Retinal thickness study with optical coherence tomography in patients with diabetes. , 2002, Investigative ophthalmology & visual science.

[127]  Quan Dong Nguyen,et al.  Persistent diabetic macular edema is associated with elevated hemoglobin A1c. , 2005, American journal of ophthalmology.

[128]  B. Klein,et al.  Global Prevalence and Major Risk Factors of Diabetic Retinopathy , 2012, Diabetes Care.

[129]  Marco A Zarbin,et al.  Diabetic macular edema: pathogenesis and treatment. , 2009, Survey of ophthalmology.

[130]  A Erginay,et al.  Reproducibility of retinal mapping using optical coherence tomography. , 2001, Archives of ophthalmology.

[131]  S. Maria,et al.  Repeatability and reproducibility of fast macular thickness mapping with stratus optical coherence tomography , 2006 .

[132]  Michael Larsen,et al.  Diabetic macular edema assessed with optical coherence tomography and stereo fundus photography. , 2002, Investigative ophthalmology & visual science.

[133]  U. Aftab,et al.  Automated identification of exudates for detection of macular edema , 2012, 2012 Cairo International Biomedical Engineering Conference (CIBEC).

[134]  Edoardo Midena,et al.  Diabetic macular edema: fundus autofluorescence and functional correlations. , 2011, Investigative ophthalmology & visual science.

[135]  David J Browning,et al.  Comparison of the clinical diagnosis of diabetic macular edema with diagnosis by optical coherence tomography. , 2004, Ophthalmology.

[136]  T. Williamson,et al.  Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. , 1996, The British journal of ophthalmology.

[137]  Desislava Koleva-Georgieva,et al.  Assessment of serous macular detachment in eyes with diabetic macular edema by use of spectral-domain optical coherence tomography , 2009, Graefe's Archive for Clinical and Experimental Ophthalmology.

[138]  Adisom Leelasantitham,et al.  Automated classification between age-related macular degeneration and Diabetic macular edema in OCT image using image segmentation , 2014, The 7th 2014 Biomedical Engineering International Conference.

[139]  Omer Faruk Sahin,et al.  Imaging in Ophthalmology , 2014 .

[140]  Zofia Mariak,et al.  Can optical coherence tomography replace fluorescein angiography in detection of ischemic diabetic maculopathy? , 2013, Graefe's Archive for Clinical and Experimental Ophthalmology.

[141]  K. Emi,et al.  Quantitative assessment of macular thickness in normal subjects and patients with diabetic retinopathy by scanning retinal thickness analyser , 1999, The British journal of ophthalmology.

[142]  S. D'Anna,et al.  Noninvasive mapping of the normal retinal thickness at the posterior pole. , 1999, Ophthalmology.

[143]  Ali Erginay,et al.  Optical coherence tomography for evaluating diabetic macular edema before and after vitrectomy. , 2003, American journal of ophthalmology.

[144]  A. Alghadyan,et al.  Diabetic retinopathy - An update. , 2011, Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological Society.

[145]  Bunyarit Uyyanonvara,et al.  Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods , 2008, Comput. Medical Imaging Graph..

[146]  E Reichel,et al.  Topography of diabetic macular edema with optical coherence tomography. , 1998, Ophthalmology.

[147]  G Richard,et al.  Optical coherence tomography for retinal thickness measurement in diabetic patients without clinically significant macular edema. , 2000, Ophthalmic surgery and lasers.

[148]  AcharyaU. Rajendra,et al.  Computer-aided diagnosis of diabetic retinopathy , 2013 .

[149]  Brian Brown,et al.  Structural and functional imaging of the retina: new ways to diagnose and assess retinal disease * , 2008, Clinical & experimental optometry.

[150]  M. U. Akram,et al.  A computer aided system for grading of maculopathy , 2012, 2012 Cairo International Biomedical Engineering Conference (CIBEC).

[151]  H. Hirakawa,et al.  Optical coherence tomography of cystoid macular edema associated with retinitis pigmentosa. , 1999, American journal of ophthalmology.

[152]  Don-Il Ham,et al.  The correlation between fluorescein angiographic and optical coherence tomographic features in clinically significant diabetic macular edema. , 2004, American journal of ophthalmology.

[153]  Sharib Ali,et al.  Exudate segmentation on retinal atlas space , 2013, 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA).

[154]  D. Weinberger,et al.  Retinal thickness variation in the diabetic patient measured by the retinal thickness analyser , 1998, The British journal of ophthalmology.

[155]  Jian Chen,et al.  Automatic and efficient detection of the fovea center in retinal images , 2014, 2014 7th International Conference on Biomedical Engineering and Informatics.

[156]  P. Campochiaro,et al.  Optical coherence tomography findings in persistent diabetic macular edema: the vitreomacular interface. , 2007, American journal of ophthalmology.

[157]  U. Rajendra Acharya,et al.  Computer-aided diagnosis of diabetic retinopathy: A review , 2013, Comput. Biol. Medicine.

[158]  T W Gardner,et al.  Diabetic retinopathy. , 1998, Diabetes care.

[159]  Jayanthi Sivaswamy,et al.  Multi-space clustering for segmentation of exudates in retinal color photographs , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[160]  Yin Aye Moe,et al.  Automatic Exudate Detection with a Naive Bayes Classifier , 2008 .

[161]  Francesco Bandello,et al.  Enhanced depth imaging optical coherence tomography in type 2 diabetes. , 2012, Investigative ophthalmology & visual science.

[162]  Hannelore Ehrenreich Autism as a disease of the synapse: search for mechanistic insight , 2015, SpringerPlus.

[163]  T. Sano,et al.  [Diabetic retinopathy]. , 2001, Nihon rinsho. Japanese journal of clinical medicine.

[164]  T. Teng,et al.  Progress towards automated diabetic ocular screening: A review of image analysis and intelligent systems for diabetic retinopathy , 2006, Medical and Biological Engineering and Computing.