- •Foreword
- •Preface
- •Contents
- •1.1 Introduction
- •1.2 Method
- •1.2.1 Databases
- •1.2.2 Dates
- •1.2.3 Keywords
- •1.2.4 Criteria for Inclusion
- •1.2.5 Criteria for Exclusion
- •1.2.6 Selection of Papers
- •1.3 Results
- •1.3.1 Subspecialty
- •1.3.2 Type of Telemedicine
- •1.3.3 Study Design
- •1.3.4 Final Conclusions of Papers
- •1.4 Discussion
- •References
- •2.1 Introduction
- •2.2 The Need for Diabetic Retinopathy Screening Programs
- •2.4 Guidelines for Referring Patients
- •2.7 Program Models for Diabetic Retinopathy Screening
- •2.9 Program Personnel and Operations
- •2.9.1 Primary Care Providers
- •2.9.2 Photographers
- •2.9.3 Clinical Consultants
- •2.9.4 Administrators
- •2.9.5 A Note to CEOs, Operations Directors, and Clinic Managers
- •2.10 Policies and Procedures
- •2.10.1 Sample Protocol 1
- •2.10.1.1 Diabetic Retinopathy Screening Services
- •Policy
- •Background
- •Procedure
- •2.10.2 Sample Protocol 2
- •2.10.2.1 Pupil Dilation Before Diabetic Retinopathy Photography
- •Policy
- •Background
- •Procedure
- •2.10.3 Sample Protocol 3
- •2.10.3.1 Diabetic Retinopathy Photography Review
- •Policy
- •Background
- •Procedure
- •2.11 Technical Requirements
- •2.11.1 Connectivity
- •2.11.2 Resolution
- •2.11.3 Color
- •2.11.4 Stereopsis
- •2.11.5 Compression
- •2.11.6 Enhancement
- •2.11.7 Pupil Dilation
- •2.11.8 Early California Telemedicine Initiatives Diabetic Retinopathy Screening
- •2.11.9 The American Indian Diabetes Teleophthalmology Grant Program
- •2.11.10 Central Valley EyePACS Diabetic Retinopathy Screening Project
- •2.12.1 Diabetic Retinopathy
- •2.12.1.1 ADA Guidelines Terms
- •2.12.1.2 Vitrectomy
- •References
- •3: Stereopsis and Teleophthalmology
- •3.1 Introduction
- •3.2 History of Stereopsis and Stereopsis in Ophthalmology
- •3.3 Technology and Photography
- •3.3.3 Imaging Fields
- •3.3.4 Image Viewing Techniques
- •3.3.5 Image Compression
- •3.4 Stereoscopic Teleophthalmology Systems
- •3.4.1 University of Alberta
- •3.4.4 Joslin Vision Network
- •3.5 Conclusion
- •References
- •4.1 Introduction
- •4.2 Methods
- •4.2.1 Main Outcome Measures
- •4.3 Results
- •4.3.1 Retinal Video Recording Versus Retinal Still Photography
- •4.3.2 Video Compression Analysis
- •4.4 Discussion
- •References
- •5.1 Introduction
- •5.1.1 Automated, Remote Image Analysis of Retinal Diseases
- •5.1.2 Telehealth
- •5.2 Design Requirements
- •5.2.1 Telehealth Network Architecture
- •5.2.2 Work Flow
- •5.2.3 Performance Evaluation of the Network
- •5.3 Automated Image Analysis Overview
- •5.3.1 Quality Assessment Module
- •5.3.2 Vascular Tree Segmentation
- •5.3.3 Quality Evaluation
- •5.4 Anatomic Structure Segmentation
- •5.4.1 Optic Nerve Detection
- •5.4.2 Macula
- •5.4.3 Lesion Segmentation
- •5.4.4 Lesion Population Description
- •5.4.5 Image Query
- •5.5 Summary
- •References
- •6.1 Introduction
- •6.3 Optical Coherence Tomography to Detect Leakage
- •References
- •7.1 Introduction
- •7.2 Patients and Methods
- •7.2.1 Participants
- •7.2.2 Methods
- •7.2.3 Statistics
- •7.3 Results
- •7.3.1 Reliability of Image Evaluation
- •7.3.2 Prevalence of Glaucomatous Optic Nerve Atrophy
- •7.4 Discussion
- •7.5 Perspectives
- •References
- •8.1 Introduction
- •8.1.2 Homology Between Retinal and Systemic Microvasculature
- •8.1.3 Need for More Precise CVD Risk Prediction
- •8.2.1 Retinal Microvascular Signs
- •8.2.2 Retinal Vessel Biometry
- •8.2.3 Newer Retinal Imaging for Morphologic Features of Retinal Vasculature
- •8.3 Associations of Retinal Imaging and CVD Risk
- •8.3.1.1 Risk of Pre-clinical CVD
- •8.3.1.2 Risk of Stroke
- •8.3.1.3 Risk of Coronary Heart Disease
- •8.3.2.1 Risk of Hypertension
- •8.3.2.2 Risk of Stroke
- •8.3.2.3 Risk of Coronary Heart Disease
- •8.3.2.4 Risk of Peripheral Artery Disease
- •8.3.3 Newer Morphologic Features of Retinal Vasculature
- •8.4 Retinal Imaging and Its Potential as a Tool for CVD Risk Prediction
- •References
- •9.1 Alzheimer’s Disease
- •9.2 Treatments
- •9.3 Diagnosis
- •9.6 Conclusions
- •References
- •10.1 Introduction
- •10.1.1 Stroke
- •10.1.2 Heart Disease
- •10.1.3 Arteriovenous Ratio
- •10.2 Purpose
- •10.3 Method
- •10.3.1 Medical Approach
- •10.3.2 Technical Approach
- •10.3.3 Output of Medical Data
- •10.4 Patients
- •10.5 Results
- •10.5.1 Medical History
- •10.5.2 Telemedical Evaluation of Retinal Vessels
- •10.5.2.1 Prevalence of Retinal Microangiopathy
- •10.5.2.2 Arteriovenous Ratio
- •10.5.2.3 PROCAM-Index
- •10.6 Discussion and Perceptive
- •10.6.1 Estimation of “Stroke Risk” Estimated by the Stage of Retinal Microangiopathy
- •References
- •11.1 Introduction
- •11.2 System Requirements
- •11.3 Fundus Camera
- •11.4 Imaging Procedure
- •11.4.1 Reading Center Procedure
- •11.5 Detection of Macular Edema
- •11.6 Implementation
- •11.7 Unreadable Images
- •11.7.1 Impact on Overall Diabetic Retinopathy Assessment Rates
- •11.7.2 Compliance with Recommendations
- •11.7.3 Challenges
- •11.7.4 Summary
- •References
- •12.1 Screening
- •12.2 Background
- •12.3 Historical Perspective in England
- •12.4 Methodology
- •12.4.1 The Aim of the Programme
- •12.5 Systematic DR Screening
- •12.6 Cameras for Use in the English Screening Programme
- •12.7 Software for Use in the English Screening Programme
- •12.9 Implementation in England
- •12.11 Quality Assurance
- •12.12 The Development of External Quality Assurance in the English Screening Programme
- •12.13 Information Technology (IT) Developments for the English Screening Programme
- •12.14 Dataset Development
- •12.15 The Development of External Quality Assurance Test Set for the English Screening Programme
- •12.16 Failsafe
- •12.17 The Epidemic of Diabetes
- •References
- •13.1 Introduction
- •13.2 Burden of Diabetes and Diabetic Retinopathy in India
- •13.3 Diabetic Retinopathy Screening Models
- •13.4 Need for Telescreening
- •13.5 Guidelines for Telescreening
- •13.6 ATA Categories of DR Telescreening Validation
- •13.7 Yield of Diabetic Retinopathy in a Telescreening Model
- •13.8 How Are Images Transferred
- •13.10 How Many Fields Are Enough for Diabetic Retinopathy Screening
- •13.11 Is Mydriasis Needed While Using Nonmydriatic Camera?
- •13.12 Validation Studies on Telescreening
- •13.12.1 Accuracy of Telescreening
- •13.12.2 Patient Satisfaction in Telescreening
- •13.12.3 Cost Effectivity
- •13.12.4 Telescreening for Diabetic Retinopathy: Our Experience
- •13.13 Future of Diabetic Retinopathy Screening
- •References
- •14.1 Introduction
- •14.2 Methods
- •14.3 Discussion
- •14.4 Conclusion
- •References
- •15.1 Introduction
- •15.1.1 Description of the EADRSI
- •15.5 State Support of Screening in the Safety Net
- •15.7 Screening Economics for Providers
- •15.8 Patient Sensitivity to Fees
- •15.9 Conclusion
- •References
- •16.1 Introduction
- •16.2 Setting Up the New Screening Model
- •16.2.1 Phase 1: Training
- •16.2.2 Phase 2: Evaluation of Agreement
- •16.2.3 Phase 3: Implementation of the Screening Model
- •16.3 Technologic Requirements
- •16.3.1 Data Management
- •16.3.2 Data Models
- •16.3.2.1 Data Scheme for Patient-Related Information
- •16.3.2.2 Data Scheme for Images
- •Fundus Camera VISUCAM Pro NM
- •PACS Server
- •ClearCanvas DICOM Visualizer
- •16.4 Results
- •16.4.1 Phase 2: Agreement Evaluation
- •16.4.2 Phase 3: Implementation of the Screening Model
- •16.5 Discussion
- •16.5.1 Evaluation of the Screening Model
- •16.5.2 Prevalence of DR
- •16.5.3 Quality Evaluation
- •16.6 Conclusion
- •References
- •17.1.3 Examination and Treatment
- •17.1.4 Limitations of Current Care
- •17.2 Telemedicine and ROP
- •17.2.2 Accuracy and Reliability of Telemedicine for ROP Diagnosis
- •17.2.3 Operational ROP Telemedicine Systems
- •17.2.4 Potential Barriers
- •17.3 Closing Remarks
- •17.3.1 Future Directions
- •References
- •18.1 Introduction
- •18.2 Neonatal Stress and Pain
- •18.3 ROP Screening Technique
- •18.4 Effect of Different Examination Techniques on Stress
- •18.5 Future of Retinal Imaging in Babies
- •References
- •19.1 Introduction
- •19.2 History of the Program
- •19.3 Telehealth Technologies
- •19.4 Impact of the Program
- •Selected References
- •Preamble
- •Introduction
- •Background
- •The Diabetic Retinopathy Study (DRS)
- •Mission
- •Vision
- •Goals
- •Guiding Principles
- •Ethics
- •Clinical Validation
- •Category 1
- •Category 2
- •Category 3
- •Category 4
- •Communication
- •Medical Care Supervision
- •Patient Care Coordinator
- •Image Acquisition
- •Image Review and Evaluation
- •Information Systems
- •Interoperability
- •Image Acquisition
- •Compression
- •Data Communication and Transmission
- •Computer Display
- •Archiving and Retrieval
- •Security
- •Reliability and Redundancy
- •Documentation
- •Image Analysis
- •Legal Requirements
- •Facility Accreditation
- •Privileging and Credentialing
- •Stark Act and Self-referrals
- •State Medical Practice Acts/Licensure
- •Tort Liability
- •Duty
- •Standards of Care
- •Consent
- •Quality Control
- •Operations
- •Customer Support
- •Originating Site
- •Transmission
- •Distant Site
- •Financial Factors
- •Reimbursement
- •Grants
- •Federal Programs
- •Other Financial Factors
- •Equipment Cost
- •Summary
- •Abbreviations
- •Appendices
- •Appendix A: Interoperability
- •Appendix B: DICOM Metadata
- •Appendix C: Computer-Aided Detection
- •Appendix D: Health Insurance Portability and Accountability Act (HIPAA)
- •Appendix F: Quality Control
- •Appendix H: Customer Support
- •Level 1
- •Level 2
- •Level 3
- •Appendix I: Reimbursement
- •Medicare
- •Medicaid
- •Commercial Insurance Carrier Reimbursement
- •Other Financial Factors
- •Disease Prevention
- •Resource Utilization
- •American Telemedicine Association’s Telehealth Practice Recommendations for Diabetic Retinopathy
- •Conclusion
- •References
- •Contributors
- •Second Edition
- •First Edition
- •Index
3 Stereopsis and Teleophthalmology |
35 |
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3.4.3American University of Beirut speciÞcity of 86% for exact agreement between
Medical Center
This group compared two non-mydriatic, stereoscopic 45¡ photographs of the macula and optic nerve, along with red-free images and colour images alone, to a dilated fundus examination [26]. Fourteen percent of the images were unable to be interpreted due to poor quality. They found that the addition of stereoscopic images with monochromatic views increased the sensitivity and speciÞcity (70.0% and 93.9%, respectively) for the detection of diabetic retinopathy in comparison to non-stereoscopic colour images alone.
3.4.4Joslin Vision Network
The Joslin Vision Network (JVN) teleophthalmology system uses non-mydriatic imaging to evaluate diabetic retinopathy. Their imaging system captures three 45¡ stereoscopic photographs that cover approximately 70% of the ETDRS standard seven Þelds [2, 6, 7]. Several studies have been published evaluating the detection and grading of diabetic retinopathy. Although one study showed substantial agreement (k =0.65) in the grading of diabetic retinopathy, 12% of the images were ungradable. Most of these ungradable images were a result of reduced stereo quality and therefore affected the evaluation of macular oedema [6].
Chow et al. [8] also compared their non-mydri- atic imaging in the detection of non-diabetic eye disease in diabetic patients to a dilated ophthalmic examination. They found that at least one nondiabetic ocular Þnding was discovered in 40.7% of patients, such as retinal emboli, chorioretinal atrophy or scars, choroidal lesions, epiretinal membranes, indicators of glaucoma, hypertensive retinopathy, age-related maculopathy and cataracts. There was a substantial to near perfect agreement (k 0.71 to ³0.80) between their imaging system and a dilated ophthalmic examination.
In a more recent study [2], their system was compared to a dilated fundus exam for the detection of diabetic retinopathy. Thirty-Þve percent of photographs were judged to be inadequate for grading because of lens opacities, image shadowing or misalignment. However, they found a
their digital imaging system and dilated fundus exams reviewed by record.
The JVN system incorporates non-mydriatic stereoscopic retinal photography and works to offer same-day retinal evaluation in a primary care or an endocrinology setting. While this system may have a higher percentage of ungradable images, this is a system that is striving to improve patient care in the management of diabetes mellitus.
3.5Conclusion
Stereopsis and the information that it provides are extremely important for both clinical ophthalmologists and those providing care via teleophthalmology. While some monoscopic systems have been validated for the identification of diabetic retinopathy and glaucoma, the gold standard remains stereoscopic imaging.
Teleophthalmology systems, in contrast to traditional clinical examinations, are used to extend the reach of specialists to patients that may have difÞculty accessing tertiary care. Inclusion of stereopsis in a teleophthalmology system will improve speciÞcity and reduce the number of unnecessary referrals. The technological barriers and patient discomfort from pupillary dilation, which is necessary to capture high-quality stereo photographs, are slight when compared to the beneÞts. Given the wide variety of imaging systems that can capture stereo photographs, teleophthalmology groups should consider the incorporation of stereopsis.
References
1. Diabetic Retinopathy Study. Report Number 7. A modiÞcation of the Airlie House classiÞcation of diabetic retinopathy. Invest Ophthalmol Vis Sci 1981; 21(1 Pt 2):1Ð226
2. Ahmed J, Ward TP, Bursell SE et al (2006) The sensitivity and speciÞcity of nonmydriatic digital stereoscopic retinal imaging in detecting diabetic retinopathy. Diabetes Care 29(10):2205Ð2209
3. Baker CF, Rudnisky CJ, Tennant MT et al (2004) JPEG compression of stereoscopic digital images for the diagnosis of diabetic retinopathy via teleophthalmology. Can J Ophthalmol 39(7):746Ð754
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B.K. Wong et al. |
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4. Beauregard D, Lewis J, Piccolo M et al (2000) Diagnosis of glaucoma using telemedicine Ð the effect of compression on the evaluation of optic nerve head cup-disc ratio. J Telemed Telecare 6(Suppl 1):S123ÐS125
5. Boucher MC, Desroches G, Garcia-Salinas R et al (2008) Teleophthalmology screening for diabetic retinopathy through mobile imaging units within Canada. Can J Ophthalmol 43(6):658Ð668
6. Bursell SE, Cavallerano JD, Cavallerano AA et al (2001) Stereo nonmydriatic digital-video color retinal imaging compared with early treatment diabetic retinopathy study seven standard Þeld 35-mm stereo color photos for determining level of diabetic retinopathy. Ophthalmology 108(3):572Ð585
7. Cavallerano JD, Aiello LP, Cavallerano AA et al (2005) Nonmydriatic digital imaging alternative for annual retinal examination in persons with previously documented no or mild diabetic retinopathy. Am J Ophthalmol 140(4):667Ð673
8. Chow SP, Aiello LM, Cavallerano JD et al (2006) Comparison of nonmydriatic digital retinal imaging versus dilated ophthalmic examination for nondiabetic eye disease in persons with diabetes. Ophthalmology 113(5):833Ð840
9. Ciulla TA, Regillo CD, Harris A (2003) Retina and optic nerve imaging. Lippincott Williams & Wilkins, Philadelphia, p x, 369p
10.Fransen SR, Leonard-Martin TC, Feuer WJ et al (2002) Clinical evaluation of patients with diabetic retinopathy: accuracy of the Inoveon diabetic retinop-
athy-3DT system. Ophthalmology 109(3):595Ð601 11. Gomez-Ulla F, Alonso F, Aibar B et al (2008) A com-
parative cost analysis of digital fundus imaging and direct fundus examination for assessment of diabetic retinopathy. Telemed J E Health 14(9):912Ð918
12.Hanson C, Tennant MT, Rudnisky CJ (2008) Optometric referrals to retina specialists: evaluation and triage via teleophthalmology. Telemed J E Health 14(5):441Ð445
13.Henkes HE, Nederlands Oogheelkundig Gezelschap (1973) Photography, electro-ophthalmology and
echo-ophthalmology in ophthalmic practice. In: Henkes Harold E (ed) Documenta ophthalmologica, Proceedings series. Junk, The Hague, p v, 318p
14. Johansen MA, Fossen K, Norum J et al (2008) The potential of digital monochrome images versus colour slides in telescreening for diabetic retinopathy. J Telemed Telecare 14(1):27Ð31
15. Lee MS, Shin DS, Berger JW (2000) Grading, image analysis, and stereopsis of digitally compressed fundus images. Retina 20(3):275Ð281
16.Lehmann MV, Mardin CY, Martus P et al (2008) 3D vs 2D qualitative and semiquantitative evaluation of the glaucomatous optic disc atrophy using computerassisted stereophotography. Eye (Lond) 22(5):628Ð635
17.Li HK, Hubbard LD, Danis RP et al (2010) Monoscopic vs. stereoscopic retinal photography for grading diabetic retinopathy severity. Invest Ophthalmol Vis Sci 51(6):3184Ð3192, Epub 2010 Jan 6
18. Martinello M, Favaro P, Muyo Nieto GD et al (2007) 3-D retinal surface inference: stereo or monocular fundus camera? Conf Proc IEEE Eng Med Biol Soc 2007:896Ð899
19. Moss SE, Meuer SM, Klein R et al (1989) Are seven standard photographic Þelds necessary for classiÞcation of diabetic retinopathy? Invest Ophthalmol Vis Sci 30(5):823Ð828
20. Murgatroyd H, Ellingford A, Cox A et al (2004) Effect of mydriasis and different Þeld strategies on digital image screening of diabetic eye disease. Br J Ophthalmol 88(7):920Ð924
21.Neubauer AS, Rothschuh A, Ulbig MW et al (2008) Digital fundus image grading with the non-mydriatic visucam(PRO NM) versus the FF450(plus) camera in diabetic retinopathy. Acta Ophthalmol 86(2):177Ð182
22. Rudnisky CJ, Hinz BJ, Tennant MT et al (2002) Highresolution stereoscopic digital fundus photography versus contact lens biomicroscopy for the detection of clinically signiÞcant macular edema. Ophthalmology 109(2):267Ð274
23. Rudnisky CJ, Tennant MT, de Leon AR et al (2006) BeneÞts of stereopsis when identifying clinically signiÞcant macular edema via teleophthalmology. Can J Ophthalmol 41(6):727Ð732
24.Rudnisky CJ, Tennant MT, Weis E et al (2007) Web-based grading of compressed stereoscopic digital photography versus standard slide Þlm photography for the diagnosis of diabetic retinopathy. Ophthalmology 114(9):1748Ð1754
25.Saine PJ, Tyler ME (2002) Ophthalmic photography: retinal photography, angiography, and electronic imaging. Butterworth-Heinemann, Boston, p xv, 398p
26. Salti HI, Nasrallah M, Haddad S et al (2009) Enhancing nonmydriatic color photographs of the retina with monochromatic views and a stereo pair to detect diabetic retinopathy. Ophthalmic Surg Lasers Imaging 40(4):373Ð378
27. Scanlon PH, Foy C, Malhotra R et al (2005) The inßuence of age, duration of diabetes, cataract, and pupil size on image quality in digital photographic retinal screening. Diabetes Care 28(10):2448Ð2453
28.Scanlon PH, Malhotra R, Greenwood RH et al (2003) ComparisonoftworeferencestandardsinvalidatingtwoÞeld
mydriatic digital photography as a method of screening for diabetic retinopathy. Br J Ophthalmol 87(10):1258Ð1263 29. Somani R, Tennant M, Rudnisky C et al (2005) Comparison of stereoscopic digital imaging and slide Þlm photography in the identiÞcation of macular
degeneration. Can J Ophthalmol 40(3):293Ð302
30.Taylor CR, Merin LM, Salunga AM et al (2007) Improving diabetic retinopathy screening ratios using
telemedicine-based digital retinal imaging technology: the Vine Hill study. Diabetes Care 30(3):574Ð578
31. Tennant MT, Greve MD, Rudnisky CJ et al (2001) IdentiÞcation of diabetic retinopathy by stereoscopic digital imaging via teleophthalmology: a comparison to slide Þlm. Can J Ophthalmol 36(4):187Ð196
32.Wade NJ (2002) Charles Wheatstone (1802Ð1875). Perception 31(3):265Ð272
Video Imaging Technology: |
4 |
A Novel Method for Diabetic |
Retinopathy Screening
Daniel Ting, Kanagasingam Yogesan, Ian Constable,
and Mei-Ling Tay-Kearney
4.1Introduction
Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia and causes both macrovascular and microvascular complications. Diabetic retinopathy (DR), the commonest microvascular complication of DM,
D. Ting ( )
Information and Communication Technology Centre,
The Australian e-Health Research Centre,
Commonwealth Scientific Industrial Research
Organization (CSIRO), 65 Brockway Road,
Floreat, WA 6014, Australia
Center for Ophthalmology and Visual Sciences, Lions Eye Institute, University of Western Australia, 2 Verdun Street, Nedlands, WA 6009, Australia e-mail: daniel_ting45@hotmail.com
K. Yogesan
Ocular Health Research Group, Australian e-Health Research Centre,
CSIRO, 65 Brockway Road, Floreat, WA 6009, Australia e-mail: kan063@csiro.au
I. Constable
Vitreoretinal Service, Center for Ophthalmology and Visual Sciences, Lions Eye Institute, University of Western Australia, 2 Verdun Street,
Nedlands, WA 6009, Australia
M.-L. Tay-Kearney
Ocular Inflammation and Uveitis,
Center for Ophthalmology and Visual Sciences, Lions Eye Institute, University of Western Australia, 2 Verdun Street, Nedlands, WA 6009, Australia
occurs in 25–40% of people with type II DM [1]. It is more prevalent among the type I diabetic as more than 90% of whom will develop DR after 20 years [2].
Given that diabetes is a huge burden to the society universally, it is important that primary eye care provider can be proactive in screening for DR in the community. In the past, DR screening has been performed by dilated fundoscopy by the primary eye care providers such as the general practitioners, optometrists, and other allied health-care workers. Following that, retinal still photography using retinal cameras has become the routine screening method to screen for DR in the primary health-care setting in most countries such as United States, United Kingdom, Australia, Europe, and Singapore.
Until recently, the use of video-based imaging technology has been proposed as a novel technique for DR screening [3]. Each retinal video takes 15–20 s to perform, and it provides a continuity of retinal view from optic disk to macula and temporal views. The retinal video is performed by a simple fundus camera which has retinal video recording function. This is an easy technique which can be performed by inexperienced personnel with minimal training. The purpose of this study is to evaluate the efficacy of this novel technique in screening for DR, with reference to the routine screening methods using retinal still photography and slit lamp examination (reference standard) for our study.
K. Yogesan et al. (eds.), Digital Teleretinal Screening, |
37 |
DOI 10.1007/978-3-642-25810-7_4, © Springer-Verlag Berlin Heidelberg 2012 |
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