Digital Ocular Fundus Imaging: A Review

Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs.

[1]  Hong Shen,et al.  Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms , 1999, IEEE Transactions on Information Technology in Biomedicine.

[2]  J. Cunha-Vaz,et al.  Mapping retinal fluorescein leakage with confocal scanning laser fluorometry of the human vitreous. , 1999, Archives of ophthalmology.

[3]  Francis K. H. Quek,et al.  Vessel extraction techniques and algorithms: a survey , 2003, Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings..

[4]  I. Deary,et al.  Retinal image analysis: Concepts, applications and potential , 2006, Progress in Retinal and Eye Research.

[5]  Max A. Viergever,et al.  Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes , 2008, Diabetes Care.

[6]  H. Novotny,et al.  A Method of Photographing Fluorescence in Circulating Blood in the Human Retina , 1961, Circulation.

[7]  Chanjira Sinthanayothin,et al.  Feasibility Study on Computer-Aided Screening for Diabetic Retinopathy , 2006, Japanese Journal of Ophthalmology.

[8]  C. Cuspidi,et al.  Retinal wall-to-lumen ratio: a new marker of endothelial function? , 2011, Journal of hypertension.

[9]  Ole Vilhelm Larsen,et al.  Screening for diabetic retinopathy using computer based image analysis and statistical classification , 2000, Comput. Methods Programs Biomed..

[10]  Robert H. Webb,et al.  Scanning Laser Ophthalmoscope , 1981, IEEE Transactions on Biomedical Engineering.

[11]  Kunio Doi,et al.  Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology , 2006, Physics in medicine and biology.

[12]  L. Bour,et al.  Fundus photography for measurement of macular pigment density distribution in children. , 2002, Investigative ophthalmology & visual science.

[13]  Gwénolé Quellec,et al.  Detection of lesions in retina photographs based on the wavelet transform , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  A. Fercher,et al.  Performance of fourier domain vs. time domain optical coherence tomography. , 2003, Optics express.

[15]  Asoke K. Nandi,et al.  Automated localisation of retinal optic disk using Hough transform , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[16]  R. Zeimer,et al.  A fundus camera dedicated to the screening of diabetic retinopathy in the primary-care physician's office. , 2002, Investigative ophthalmology & visual science.

[17]  Timothy Q. Duong,et al.  Blood-flow magnetic resonance imaging of the retina , 2008, NeuroImage.

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

[19]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[20]  U. Rajendra Acharya,et al.  Automated Diagnosis of Glaucoma Using Digital Fundus Images , 2009, Journal of Medical Systems.

[21]  A. Pinz,et al.  Mapping the human retina , 1996, IEEE Transactions on Medical Imaging.

[22]  Aliaa A. A. Youssif,et al.  Optic Disc Detection From Normalized Digital Fundus Images by Means of a Vessels' Direction Matched Filter , 2008, IEEE Transactions on Medical Imaging.

[23]  José Manuel Bravo,et al.  A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features , 2011, IEEE Transactions on Medical Imaging.

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

[25]  Max A. Viergever,et al.  Image Registration for Digital Subtraction Angiography , 1999, International Journal of Computer Vision.

[26]  P. Massin,et al.  Evaluation of a new non‐mydriatic digital camera for detection of diabetic retinopathy , 2003, Diabetic medicine : a journal of the British Diabetic Association.

[27]  Hiroshi Fujita,et al.  Automated detection and classification of major retinal vessels for determination of diameter ratio of arteries and veins , 2010, Medical Imaging.

[28]  Timothy J. Holmes,et al.  3-D reconstruction of blood vessels in the ocular fundus from confocal scanning laser ophthalmoscope ICG angiography , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[29]  Joachim H. Nagel,et al.  Modeling Of High Resolution Digital Retinal Imaging , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[30]  J. Boyce,et al.  Automated detection of diabetic retinopathy in digital retinal images: a tool for diabetic retinopathy screening , 2004, Diabetic medicine : a journal of the British Diabetic Association.

[31]  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.

[32]  B. Masters,et al.  Fractal analysis of the vascular tree in the human retina. , 2004, Annual review of biomedical engineering.

[33]  K. Khunti,et al.  Effectiveness of screening and monitoring tests for diabetic retinopathy – a systematic review , 2000, Diabetic medicine : a journal of the British Diabetic Association.

[34]  Comparison of a digital retinal imaging system and seven-field stereo color fundus photography to detect diabetic retinopathy in the primary care environment. , 2005, Ophthalmic surgery, lasers & imaging : the official journal of the International Society for Imaging in the Eye.

[35]  Ana Maria Mendonça,et al.  Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction , 2006, IEEE Transactions on Medical Imaging.

[36]  Christos Haritoglou,et al.  Light-absorbing properties and osmolarity of indocyanine-green depending on concentration and solvent medium. , 2003, Investigative ophthalmology & visual science.

[37]  Stephen A. Burns,et al.  Infrared imaging of sub-retinal structures in the human ocular fundus , 1996, Vision Research.

[38]  José Cunha-Vaz,et al.  Measurement and Mapping of Retinal Leakage and Retinal Thickness - Surrogate Outcomes for the Initial Stages of Diabetic Retinopathy , 2002 .

[39]  Qin Li,et al.  Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs , 2010, IEEE Transactions on Medical Imaging.

[40]  Emanuele Trucco,et al.  Max-Min Central Vein Detection in Retinal Fundus Images , 2006, 2006 International Conference on Image Processing.

[41]  R V North,et al.  Digital imaging of the optic nerve head: monoscopic and stereoscopic analysis , 2005, British Journal of Ophthalmology.

[42]  Daniel Kondermann,et al.  Blood vessel classification into arteries and veins in retinal images , 2007, SPIE Medical Imaging.

[43]  Zhu HongQing Segmentation of blood vessels in retinal images using 2D entropies of gray level-gradient cooccurrence matrix , 2004 .

[44]  Rui Bernardes,et al.  Computer-Assisted Microaneurysm Turnover in the Early Stages of Diabetic Retinopathy , 2009, Ophthalmologica.

[45]  Roberto Marcondes Cesar Junior,et al.  Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification , 2005, ArXiv.

[46]  L. Gagnon,et al.  RetsoftPlus: a tool for retinal image analysis , 2004, Proceedings. 17th IEEE Symposium on Computer-Based Medical Systems.

[47]  Bram van Ginneken,et al.  Automatic detection of red lesions in digital color fundus photographs , 2005, IEEE Transactions on Medical Imaging.

[48]  Jayanthi Sivaswamy,et al.  Unsupervised curvature-based retinal vessel segmentation , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[49]  Chia-Ling Tsai,et al.  Vascular Tree Construction with Anatomical Realism for Retinal Images , 2009, 2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering.

[50]  Richard I. Hartley,et al.  Tracking of Blood Vessels in Retinal Images Using Kalman Filter , 2008, 2008 Digital Image Computing: Techniques and Applications.

[51]  B Lindblom,et al.  Confocal fundus imaging with a scanning laser ophthalmoscope in eyes with cataract. , 1995, The British journal of ophthalmology.

[52]  Alfredo Ruggeri,et al.  A divide et impera strategy for automatic classification of retinal vessels into arteries and veins , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[53]  Michael D. Ober,et al.  Ophthalmic fundus imaging: today and beyond. , 2004, American journal of ophthalmology.

[54]  Nicholas Ayache,et al.  Medical Image Analysis: Progress over Two Decades and the Challenges Ahead , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[55]  P. Desprez,et al.  Use of digital camera imaging of eye fundus for telemedicine in children suspected of abusive head injury , 2008, British Journal of Ophthalmology.

[56]  P F Sharp,et al.  An image-processing strategy for the segmentation and quantification of microaneurysms in fluorescein angiograms of the ocular fundus. , 1996, Computers and biomedical research, an international journal.

[57]  Atam P Dhawan,et al.  Optical Imaging Modalities for Biomedical Applications , 2010, IEEE Reviews in Biomedical Engineering.

[58]  A. Kampik,et al.  In vivo characterization of ischemic retina in diabetic retinopathy , 2010, Clinical ophthalmology.

[59]  P. Sharp,et al.  Laser imaging of the retina , 1999, The British journal of ophthalmology.

[60]  Heinrich Niemann,et al.  Automated Calculation of Retinal Arteriovenous Ratio for Detection and Monitoring of Cerebrovascular Disease Based on Assessment of Morphological Changes of Retinal Vascular System , 2002, MVA.

[61]  Mohd Zulfaezal Che Azemin,et al.  Robust Methodology for Fractal Analysis of the Retinal Vasculature , 2011, IEEE Transactions on Medical Imaging.

[62]  Badrinath Roysam,et al.  Integrated Analysis of Vascular and Nonvascular Changes From Color Retinal Fundus Image Sequences , 2007, IEEE Transactions on Biomedical Engineering.

[63]  Panos Liatsis,et al.  Vessel Extraction in Fluorescein Angiograms of the Human Retina Using a Supervised Classifier , 2010, 2010 Developments in E-systems Engineering.

[64]  Efficacy and reliability of fundus digital camera as a screening tool for diabetic retinopathy in Kuwait. , 2003, Journal of diabetes and its complications.

[65]  Usha Chakravarthy,et al.  Grading of age-related maculopathy for epidemiological studies: is digital imaging as good as 35-mm film? , 2003, Ophthalmology.

[66]  R. Ryder,et al.  Is Digital Retinal Imaging Alone Sufficient as a Screening Tool for Diabetic Retinopathy , 2000 .

[67]  J. Cunha-Vaz,et al.  Alterations of the blood-retinal barrier and retinal thickness in preclinical retinopathy in subjects with type 2 diabetes. , 2000, Archives of ophthalmology.

[68]  Gwénolé Quellec,et al.  Optimal Filter Framework for Automated, Instantaneous Detection of Lesions in Retinal Images , 2011, IEEE Transactions on Medical Imaging.

[69]  Larry D Hubbard,et al.  Brightness, contrast, and color balance of digital versus film retinal images in the age-related eye disease study 2. , 2008, Investigative ophthalmology & visual science.

[70]  Enrico Grisan,et al.  Detection of optic disc in retinal images by means of a geometrical model of vessel structure , 2004, IEEE Transactions on Medical Imaging.

[71]  U. Rajendra Acharya,et al.  Automated Identification of Diabetic Retinopathy Stages Using Digital Fundus Images , 2008, Journal of Medical Systems.

[72]  J. Fujimoto,et al.  In vivo ultrahigh-resolution optical coherence tomography. , 1999, Optics letters.

[73]  D. Flanagan,et al.  Is screening with digital imaging using one retinal view adequate? , 2003, Eye.

[74]  D. Ts'o,et al.  Blood contrast agents enhance intrinsic signals in the retina: evidence for an underlying blood volume component. , 2011, Investigative ophthalmology & visual science.

[75]  Ralf Brinkmann,et al.  Noninvasive Imaging and Monitoring of Retinal Pigment Epithelium Patterns Using Fundus Autofluorescence - Review , 2005 .

[76]  J. Wolffsohn,et al.  The effect of digital image resolution and compression on anterior eye imaging , 2005, British Journal of Ophthalmology.

[77]  M. Brezinski Optical Coherence Tomography: Principles and Applications , 2006 .

[78]  U. Rajendra Acharya,et al.  Identification of different stages of diabetic retinopathy using retinal optical images , 2008, Inf. Sci..

[79]  Herbert F. Jelinek,et al.  USING THE 2-D MORLET WAVELET WITH SUPERVISED CLASSIFICATION FOR RETINAL VESSEL SEGMENTATION , 2005 .

[80]  Milan Sonka,et al.  Vessel Boundary Delineation on Fundus Images Using Graph-Based Approach , 2011, IEEE Transactions on Medical Imaging.

[81]  Robert Finger,et al.  Structure-Function Correlation of the Human Central Retina , 2010, PloS one.

[82]  T. Bennett,et al.  Ophthalmic imaging today: an ophthalmic photographer's viewpoint – a review , 2009, Clinical & experimental ophthalmology.

[83]  Federico Bizzarri,et al.  DSP implementation of a low-complexity algorithm for real-time automated vessel detection in images of the fundus of the human retina , 2007, 2007 IEEE International Symposium on Circuits and Systems.

[84]  J. Fujimoto,et al.  Ultrahigh-resolution ophthalmic optical coherence tomography , 2001, Nature Medicine.

[85]  U. Rajendra Acharya,et al.  Application of Higher Order Spectra for the Identification of Diabetes Retinopathy Stages , 2008, Journal of Medical Systems.

[86]  Roberto Marcondes Cesar Junior,et al.  Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification , 2005, IEEE Transactions on Medical Imaging.

[87]  M. Larsen,et al.  Automated detection of fundus photographic red lesions in diabetic retinopathy. , 2003, Investigative ophthalmology & visual science.

[88]  P. Pani,et al.  GEMS: Underwater spectrometer for long-term radioactivity measurements , 2011 .

[89]  G S Rubin,et al.  Fundus autofluorescence imaging compared with different confocal scanning laser ophthalmoscopes , 2002, The British journal of ophthalmology.

[90]  G J Klein,et al.  An image processing approach to characterizing choroidal blood flow. , 1990, Investigative ophthalmology & visual science.

[91]  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.

[92]  U. Rajendra Acharya,et al.  Imaging Systems of Human Eye: A Review , 2008, Journal of Medical Systems.

[93]  U. Schmidt-Erfurth,et al.  Three-dimensional topographic angiography in chorioretinal vascular disease. , 2001, Investigative ophthalmology & visual science.

[94]  P F Sharp,et al.  The scanning laser ophthalmoscope--a review of its role in bioscience and medicine. , 2004, Physics in medicine and biology.

[95]  R.S. Rajesh,et al.  A reversible watermarking with low warping: An application to digital fundus image , 2008, 2008 International Conference on Computer and Communication Engineering.

[96]  T. Kivelä,et al.  Sensitivity and specificity of digital retinal images in grading diabetic retinopathy. , 2004, Acta ophthalmologica Scandinavica.

[97]  Bram van Ginneken,et al.  Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs , 2009, IEEE Transactions on Medical Imaging.

[98]  J. Cunha-Vaz,et al.  Three-year follow-up study of blood-retinal barrier and retinal thickness alterations in patients with type 2 diabetes mellitus and mild nonproliferative diabetic retinopathy. , 2004, Archives of ophthalmology.

[99]  Tatijana Stosic,et al.  Multifractal analysis of human retinal vessels , 2006, IEEE Transactions on Medical Imaging.

[100]  Lene Martin,et al.  Measurement of optic disc parameters on digital fundus photographs: algorithm development and evaluation , 2008, Acta ophthalmologica.

[101]  Yueh-Min Huang,et al.  A novel approach to diagnose diabetes based on the fractal characteristics of retinal images , 2003, IEEE Transactions on Information Technology in Biomedicine.

[102]  Ana Maria Mendonça,et al.  Automatic segmentation of microaneurysms in retinal angiograms of diabetic patients , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[103]  P. Mitchell,et al.  Retinal Vascular Imaging: A New Tool in Microvascular Disease Research , 2008, Circulation. Cardiovascular imaging.

[104]  A. Bird,et al.  FUNDUS AUTOFLUORESCENCE IMAGING: Review and Perspectives , 2008, Retina.

[105]  Jean-Yves Catros,et al.  An artificial intelligence approach for medical picture analysis , 1988, Pattern Recognit. Lett..

[106]  M. Tyrberg,et al.  Colour slides or digital photography in diabetes screening--a comparison. , 2000, Acta ophthalmologica Scandinavica.

[107]  Manuel G. Penedo,et al.  Retinal vessel tree segmentation using a deformable contour model , 2008, 2008 19th International Conference on Pattern Recognition.

[108]  Cathy R. Taylor,et al.  Improving Diabetic Retinopathy Screening Ratios Using Telemedicine-Based Digital Retinal Imaging Technology , 2007, Diabetes Care.

[109]  R. C. Tripathi,et al.  Automated Early Detection of Diabetic Retinopathy Using Image Analysis Techniques , 2010 .

[110]  Esther de Ves,et al.  Segmentation of macular fluorescein angiographies. A statistical approach , 2001, Pattern Recognit..

[111]  Charles V. Stewart,et al.  A Feature-Based, Robust, Hierarchical Algorithm for Registering Pairs of Images of the Curved Human Retina , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[112]  M. Sasa,et al.  A Three-year Follow-up Study , 1981 .

[113]  A. Mead,et al.  Diabetic retinal screening in the UK , 2001, Journal of the Royal Society of Medicine.

[114]  B. Roysam,et al.  Image processing algorithms for retinal montage synthesis, mapping, and real-time location determination , 1998, IEEE Transactions on Biomedical Engineering.

[115]  Peter K Kaiser,et al.  Oscillation of angiogenesis with vascular dropout in diabetic retinopathy by VESsel GENeration analysis (VESGEN). , 2010, Investigative ophthalmology & visual science.

[116]  Mong-Li Lee,et al.  A piecewise Gaussian model for profiling and differentiating retinal vessels , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[117]  Badrinath Roysam,et al.  Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.

[118]  Sameh A. Salem,et al.  Segmentation of retinal blood vessels based on analysis of the hessian matrix and Clustering Algorithm , 2007, 2007 15th European Signal Processing Conference.

[119]  Bashir Al-Diri,et al.  Automated analysis of retinal vascular network connectivity , 2010, Comput. Medical Imaging Graph..

[120]  J. López‐Bastida,et al.  Sensitivity and specificity of digital retinal imaging for screening diabetic retinopathy , 2007, Diabetic medicine : a journal of the British Diabetic Association.

[121]  A. Ting,et al.  Comparison of stereoscopic digital imaging and slide film photography in the identification of macular degeneration. , 2005, Canadian journal of ophthalmology. Journal canadien d'ophtalmologie.

[122]  M. Larsen,et al.  Automated detection of diabetic retinopathy in a fundus photographic screening population. , 2003, Investigative ophthalmology & visual science.

[123]  Qifa Zhou,et al.  Photoacoustic ophthalmoscopy for in vivo retinal imaging , 2010, Optics express.

[124]  Marius Cristian Luculescu,et al.  Computer-aided diagnosis system for retinal diseases in medical imaging , 2008 .

[125]  Introduction to Ocular Fluorometry , 1993 .

[126]  Herbert F. Jelinek,et al.  Towards vessel characterisation in the vicinity of the optic disc in digital retinal images , 2005 .

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

[128]  Lloyd Paul Aiello,et al.  Telemedicine and Diabetic Retinopathy , 2011 .

[129]  T. Sheidow,et al.  Prospective evaluation of digital non-stereo color fundus photography as a screening tool in age-related macular degeneration. , 2005, American journal of ophthalmology.

[130]  Ganga Karunamuni,et al.  VESGEN 2D: Automated, User‐Interactive Software for Quantification and Mapping of Angiogenic and Lymphangiogenic Trees and Networks , 2009, Anatomical record.

[131]  V. Jeganathan Evaluation of Digital Fundus images as a diagnostic method for surveillance of diabetic retinopathy. , 2008, Military medicine.

[132]  J. Lim,et al.  A comparison of digital nonmydriatic fundus imaging with standard 35-millimeter slides for diabetic retinopathy. , 2000, Ophthalmology.

[133]  P. Mitchell,et al.  Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy , 2009 .

[134]  Shijian Lu,et al.  Automatic Optic Disc Detection From Retinal Images by a Line Operator , 2011, IEEE Transactions on Biomedical Engineering.

[135]  Jacob Scharcanski,et al.  Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach , 2010, Comput. Biol. Medicine.

[136]  Michael Larsen,et al.  Assessment of Automated Screening for Treatment-Requiring Diabetic Retinopathy , 2007, Current eye research.

[137]  Andrew R. Harvey,et al.  New spectral imaging techniques for blood oximetry in the retina , 2007, European Conference on Biomedical Optics.

[138]  P. Artal,et al.  Chromatic aberration correction of the human eye for retinal imaging in the near infrared. , 2006, Optics express.

[139]  Yasser M. Kadah,et al.  A new real-time retinal tracking system for image-guided laser treatment , 2002, IEEE Transactions on Biomedical Engineering.

[140]  Rui Bernardes,et al.  Mapping the human blood-retinal barrier function , 2005, IEEE Transactions on Biomedical Engineering.

[141]  Xiaoyi Jiang,et al.  Separation of the retinal vascular graph in arteries and veins based upon structural knowledge , 2009, Image Vis. Comput..

[142]  Martin Hoheisel,et al.  Review of medical imaging with emphasis on X-ray detectors , 2006 .

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

[144]  Samuel C. Lee,et al.  Computer classification of nonproliferative diabetic retinopathy. , 2005, Archives of ophthalmology.

[145]  P. Sharp,et al.  Automated detection and quantification of microaneurysms in fluorescein angiograms , 2004, Graefe's Archive for Clinical and Experimental Ophthalmology.

[146]  I. Indrajit Digital imaging and communications in medicine: A basic review , 2007 .

[147]  T. Peto,et al.  What is lost by digitizing stereoscopic fundus color slides for macular grading in age-related maculopathy and degeneration? , 2004, Ophthalmology.

[148]  S. Kato,et al.  Color Doppler imaging of retinal diseases. , 2010, Survey of ophthalmology.

[149]  Paul G. Updike,et al.  Quantitative fluorescein angiographic analysis of choroidal neovascular membranes: validation and correlation with visual function. , 2007, Investigative ophthalmology & visual science.

[150]  R. Klein,et al.  Retinal venular diameter as an early indicator of progression to proliferative diabetic retinopathy with and without high-risk characteristics in African Americans with type 1 diabetes mellitus. , 2011, Archives of ophthalmology.

[151]  E. Sutter,et al.  The fine structure of multifocal ERG topographies. , 2002, Journal of vision.

[152]  Gwénolé Quellec,et al.  Automated early detection of diabetic retinopathy. , 2010, Ophthalmology.

[153]  M. Lawrence,et al.  The accuracy of digital-video retinal imaging to screen for diabetic retinopathy: an analysis of two digital-video retinal imaging systems using standard stereoscopic seven-field photography and dilated clinical examination as reference standards. , 2004, Transactions of the American Ophthalmological Society.

[154]  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.

[155]  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.

[156]  J. Forrester,et al.  Fundus autofluorescence in the diagnosis of cystoid macular oedema , 2008, British Journal of Ophthalmology.

[157]  D. Wallace,et al.  Systematic Review of Digital Imaging Screening Strategies for Retinopathy of Prematurity , 2008, Pediatrics.

[158]  Yannis A. Tolias,et al.  A fuzzy vessel tracking algorithm for retinal images based on fuzzy clustering , 1998, IEEE Transactions on Medical Imaging.

[159]  Wolfgang Drexler,et al.  High resolution in vivo intra-arterial imaging with optical coherence tomography , 1999, Photonics West - Biomedical Optics.

[160]  B. Singer,et al.  Improvement in retinal image quality with dynamic correction of the eye's aberrations. , 2001, Optics express.

[161]  J. Olson,et al.  Automated detection of microaneurysms in digital red‐free photographs: a diabetic retinopathy screening tool , 2000, Diabetic medicine : a journal of the British Diabetic Association.

[162]  N. Bressler Evaluating new retinal imaging techniques. , 1998, Archives of ophthalmology.

[163]  Hong Yan,et al.  A Novel Vessel Segmentation Algorithm for Pathological Retina Images Based on the Divergence of Vector Fields , 2008, IEEE Transactions on Medical Imaging.

[164]  Steffen Schmitz-Valckenberg,et al.  Fundus autofluorescence and progression of age-related macular degeneration. , 2009, Survey of ophthalmology.

[165]  S. Prasad,et al.  Digital photography in medicine. , 2003, Journal of postgraduate medicine.

[166]  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.

[167]  Justin Starren,et al.  Accuracy and reliability of remote retinopathy of prematurity diagnosis. , 2006, Archives of ophthalmology.

[168]  Rui Bernardes,et al.  Nonproliferative retinopathy in diabetes type 2. Initial stages and characterization of phenotypes , 2005, Progress in Retinal and Eye Research.

[169]  Justin Pedro,et al.  Simultaneous OCT/SLO/ICG imaging. , 2009, Investigative ophthalmology & visual science.

[170]  Amelia Simó,et al.  Bayesian detection of the fovea in eye fundus angiographies , 1999, Pattern Recognit. Lett..

[171]  Joseph M. Schmitt,et al.  Optical coherence tomography (OCT): a review , 1999 .

[172]  Charles V. Stewart,et al.  Predictive scheduling algorithms for real-time feature extraction and spatial referencing: application to retinal image sequences , 2004, IEEE Transactions on Biomedical Engineering.

[173]  J. Cunha-Vaz,et al.  One-year follow-up of blood-retinal barrier and retinal thickness alterations in patients with type 2 diabetes mellitus and mild nonproliferative retinopathy. , 2001, Archives of ophthalmology.

[174]  Rui Bernardes,et al.  Microaneurysm Turnover Is a Biomarker for Diabetic Retinopathy Progression to Clinically Significant Macular Edema: Findings for Type 2 Diabetics with Nonproliferative Retinopathy , 2009, Ophthalmologica.

[175]  Andrés G. Marrugo,et al.  Retinal image analysis: preprocessing and feature extraction , 2011 .