Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2014

Open Access 01-12-2014 | Research article

A survey on computer aided diagnosis for ocular diseases

Authors: Zhuo Zhang, Ruchir Srivastava, Huiying Liu, Xiangyu Chen, Lixin Duan, Damon Wing Kee Wong, Chee Keong Kwoh, Tien Yin Wong, Jiang Liu

Published in: BMC Medical Informatics and Decision Making | Issue 1/2014

Login to get access

Abstract

Background

Computer Aided Diagnosis (CAD), which can automate the detection process for ocular diseases, has attracted extensive attention from clinicians and researchers alike. It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients.

Method

We review ocular CAD methodologies for various data types. For each data type, we investigate the databases and the algorithms to detect different ocular diseases. Their advantages and shortcomings are analyzed and discussed.

Result

We have studied three types of data (i.e., clinical, genetic and imaging) that have been commonly used in existing methods for CAD. The recent developments in methods used in CAD of ocular diseases (such as Diabetic Retinopathy, Glaucoma, Age-related Macular Degeneration and Pathological Myopia) are investigated and summarized comprehensively.

Conclusion

While CAD for ocular diseases has shown considerable progress over the past years, the clinical importance of fully automatic CAD systems which are able to embed clinical knowledge and integrate heterogeneous data sources still show great potential for future breakthrough.
Appendix
Available only for authorised users
Literature
1.
Robinson BE: Prevalence of asymptomatic eye disease . Can J Optom. 2003, 65 (5): 175-180.
2.
National Eye Institute: Don’t lose sight of diabetic eye disease: information for people with diabetes . NIH Publ. 2004, 04: 3252-
3.
Fujita H, Uchiyama Y, Nakagawa T, Fukuoka D, Hatanaka Y, Hara T, Lee G, Hayashi Y, Ikedo Y, Gao X, Zhou X: Computer-aided diagnosis: The emerging of three CAD systems induced by Japanese health care needs . Comput Methods Prog Biomed. 2008, 92: 238-248.
4.
Wong T, Knudtson M, Klein R, Klein B, Meuer S, Hubbard L: Computer-assisted measurement of retinal vessel diameters in the Beaver Dam Eye Study: methodology, correlation between eyes, and effect of refractive errors . Ophthalmology. 2004, 111 (6): 1183-1190.PubMed
5.
Cheung C, Zheng Y, Hsu W, Lee M, Lau Q, Mitchell P, Wang J, Klein R, Wong T: Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors . Ophthalmology. 2011, 118 (5): 812-818.PubMed
6.
Perumalsamy N, Prasad N, Sathya S, Ramasamy K: Software for reading and grading diabetic retinopathy: Aravind diabetic retinopathy screening 3.0 . Diabetes Care. 2007, 30 (9): 2302-2306.PubMed
7.
8.
Sommer A, Tielsch JM, Katz J, Quigley HA, Gottsch JD, Javitt J, Singh K: Relationship between intraocular pressure and primary open angle glaucoma among white and black Americans. The Baltimore Eye Survey . Arch ophthalmol. 1991, 109 (8): 1090-1095.PubMed
9.
Wong TY, Klein R, Klein BE, Tielsch JM, Hubbard L, Nieto FJ: Retinal microvascular abnormalities and their relationship with hypertension, cardiovascular disease, and mortality . Surv Ophthalmol. 2001, 46 (1): 59-80.PubMed
10.
Colenbrander A: Measuring vision and vision loss. Duane’s Ophthalmology. 2009, Philadelphia, PA: Lippincott Williams & Wilkins
11.
Makeeva OA, Markova VV, Puzyrev VP: Public interest and expectations concerning commercial genotyping and genetic risk assessment . Personalized Med. 2009, 6 (3): 329-341.
12.
Abràmoff MD, Garvin MK, Sonka M: Retinal imaging and image analysis . IEEE Rev Biomed Eng. 2010, 3: 169-208.PubMed
13.
Bernardes R, Serranho P, Lobo C: Digital ocular fundus imaging: a review . Ophthalmologica. 2011, 226 (4): 161-181.PubMed
14.
Weiss S, Kulikowski C, Amarel S, Safir A: A model-based method for computer-aided medical decision making . Artif Intell. 1978, 11: 145-72.
15.
Kulikowski CA, Weiss SM: Representation of expert knowledge for consultation: the CASNET and EXPERT projects . Artif Intell Med. 1982, 51 ,
16.
Chan K, Lee TW, Sample PA, Goldbaum MH, Weinreb RN, Sejnowski TJ: Comparison of machine learning and traditional classifiers in glaucoma diagnosis . IEEE Trans Biomed Eng. 2002, 49 (9): 963-974.PubMed
17.
Bizios D, Heijl A, Bengtsson B: Integration and fusion of standard automated perimetry and optical coherence tomography data for improved automated glaucoma diagnostics . BMC Ophthalmology. 2011, 11 (1): 20-PubMedPubMedCentral
18.
Kourkoutas D, Karanasiou IS, Tsekouras G, Moshos M, Iliakis E, Georgopoulos G: Glaucoma risk assessment using a non-linear multivariable regression method . Comput Methods Programs Biomed. 2012, 108 (3): 1149-59.PubMed
19.
Liu J, Zhang Z, Wong D, Xu Y, Yin F, Cheng J, Tan N, Kwoh C, Xu D, Tham Y, Aung T, Wong T: Automatic glaucoma diagnosis through medical imaging informatics . J Am Med Assoc. 2013, 20 (6): 1021-7.
20.
Zhang Z, Xu Y, Liu J, Wong DWK, Kwoh CK, Shaw SM, Wong TY: Automatic diagnosis of pathological myopia from heterogeneous biomedical data . PLoS ONE. 2013, 8 (6): e65736-PubMedPubMedCentral
21.
World Health Organization: Blinding trachoma fact sheet . 2014,
22.
World Health Organization: Onchocerciasis fact sheet . 2014,
23.
Attebo K, Mitchell P, Smith M: Visual acuity and the causes of visual loss in Australia . Ophthalmology. 1996, 103 (3): 357-64.PubMed
24.
Foong A, Saw S, Loo J, Shen S, Loon S, Rosman M, Aung T, Tan D, Tai E, Wong T: Rationale and methodology for a population-based study of eye diseases in Malay people: The Singapore Malay eye study (SiMES) . Ophthalmic Epidemiol. 2007, 14: 25-35.PubMed
25.
Pan CW, Wong TY, Chang L, Lin XY, Lavanya R, Zheng YF, Kok YO, Wu RY, Aung T, Saw SM: Ocular biometry in an urban Indian population: the Singapore Indian eye study (SINDI) . Invest Ophthalmol Vis Sci. 2011, 52 (9): 6636-6642.PubMed
26.
Sng CC, Foo LL, Cheng CY, Allen JC, He M, Krishnaswamy G, Nongpiur ME, Friedman DS, Wong TY, Aung T: Determinants of anterior chamber depth: the Singapore Chinese Eye Study . Ophthalmology. 2012, 119 (6): 1143-50.PubMed
27.
Ryan SJ, Schachat AP: Retina . Elsevier Health Sci. 2012,
28.
Matsui M, Tashiro T, Matsumoto K, Yamamoto S: A study on automatic and quantitative diagnosis of fundus photographs. I. Detection of contour line of retinal blood vessel images on color fundus photographs . Nippon Ganka Gakkai Zasshi. 1973, 77 (8): 907-PubMed
29.
Baudoin C, Lay B, Klein J: Automatic detection of microaneurysms in diabetic fluorescein angiography . Revue depidemiologie et de sante publique. 1984, 32 (3–4): 254-
30.
Narasimha-Iyer H, Can A, Roysam B, Stewart C, Tanenbaum H, Majerovics A, Singh H: Robust detection and classification of longitudinal changes in color retinal fundus images for monitoring diabetic retinopathy . IEEE Trans Biomed Eng. 2006, 53 (6): 1084-1098.PubMed
31.
Quellec G, Lee K, Dolejsi M, Garvin MK, Abramoff MD, Sonka M: Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula . IEEE Trans Med Imaging. 2010, 29 (6): 1321-1330.PubMedPubMedCentral
32.
Liu J, Wong D, Lim J, Li H, Tan N, Zhang Z, Wong T, Lavanya R: ARGALI: An automatic cup-to-disc ratio measurement system for glaucoma analysis using level-set image processing . Proceedings of 13th International Conference on Biomedical Engineering. 2009, Heidelberg: Springer Berlin, 559-562.
33.
Huang W, Chan KL, Li H, Lim JH, Liu J, Wong TY: A computer assisted method for nuclear cataract grading from slit-lamp images using ranking . IEEE Trans Med Imaging. 2011, 30 (1): 94-107.PubMed
34.
Saine P, Tyler M: Ophthalmic photography: retinal photography, angiography, and electronic imaging. 2004, Butterworth-Heinemann
35.
Marrugo AG, Millan MS, Cristobal G, Gabarda S, Sorel M, Sroubek F: Image analysis in modern ophthalmology: from acquisition to computer assisted diagnosis and telemedicine . SPIE Photonics Europe. 2012, Bellingham: International Society for Optics and Photonics, 84360C-84360C.
36.
Chen X, Niemeijer M, Zhang L, Lee K, Abràmoff MD, Sonka M: Three-dimensional segmentation of fluid-associated abnormalities in retinal OCT: probability constrained graph-search-graph-cut . IEEE Trans Med Imaging. 2012, 31 (8): 1521-1531.PubMedPubMedCentral
37.
Wilkins GR, Houghton OM, Oldenburg AL: Automated segmentation of intraretinal cystoid fluid in optical coherence tomography . IEEE Trans Biomed Eng. 2012, 59 (4): 1109-1114.PubMedPubMedCentral
38.
Hu Z, Niemeijer M, Lee K, Abramoff MD, Sonka M, Garvin MK: Automated segmentation of the optic disc margin in 3D optical coherence tomography images using a graph-theoretic approach . Proceedings of SPIE Conference on Medical Imaging. 2009, Bellingham: International Society for Optics and Photonics, 72620U-72620U.
39.
Hu Z, Niemeijer M, Lee K, Abramoff MD, Sonka M, Garvin MK: Automated segmentation of the optic canal in 3D spectral-domain OCT of the optic nerve head (ONH) using retinal vessel suppression . Invest Ophthalmol Vis Sci. 2009, 50 (1): 33-44.
40.
Kwon YH, Hu Z, Abramoff MD, Lee K, Garvin MK: Automated segmentation of neural canal opening and optic cup in SD-OCT images . Amer. Glaucoma Soc. 20th Annu. Meeting, Naples, FL, USA. 2010,
41.
Yun S, Bouma B: Wavelength swept lasers . Optical Coherence Tomography: Technology and Applications. Edited by: Drexler W, Fujimoto JG. 2008, New York: Springer,
42.
Grulkowski I, Liu JJ, Potsaid B, Jayaraman V, Lu CD, Jiang J, Cable AE, Duker JS, Fujimoto JG: Retinal, anterior segment and full eye imaging using ultrahigh speed swept source OCT with vertical-cavity surface emitting lasers . Biomed Optics Express. 2012, 3 (11): 2733-2751.
43.
Spaide RF, Akiba M, Ohno-Matsui K: Evaluation of peripapillary intrachoroidal cavitation with swept source and enhanced depth imaging optical coherence tomography . Retina. 2012, 32 (6): 1037-1044.PubMed
44.
Lee K, Niemeijer M, Garvin MK, Kwon YH, Sonka M, Abramoff MD: Segmentation of the optic disc in 3D-OCT scans of the optic nerve head . IEEE Trans Med Imaging. 2010, 29: 159-168.PubMed
45.
Lee K, Niemeijer M, Garvin MK, Kwon YH, Sonka M, Abramoff MD: 3D segmentation of the rim and cup in spectral-domain optical coherence tomography volumes of the optic nerve head . Proceedings of SPIE Conference on Medical Imaging. 2009, Bellingham: International Society for Optics and Photonics, 7262-7283.
46.
Abramoff MD, Lee K, Niemeijer M, Alward W, Greenlee EC, Garvin MK, Sonka M, Kwon YH: Automated segmentation of the cup and rim from spectral domain OCT of the optic nerve head . Invest Ophthalmol Vis Sci. 2009, 50 (12): 5778-5784.PubMedPubMedCentral
47.
Ohno-Matsui K, Akiba M, Modegi T, Tomita M, Ishibashi T, Tokoro T, Moriyama M: Association between shape of sclera and myopic retinochoroidal lesions in patients with pathologic myopia . Invest Ophthalmol Vis Sci. 2012, 53 (1): 6046-6061.PubMed
48.
Ohno-Matsui K, Akiba M, Moriyama M, Shimada N, Ishibashi T, Tokoro T, Spaide RF: Acquired optic nerve and peripapillary pits in pathologic myopia . Ophthalmology. 2012, 119 (8): 1685-1692.PubMed
49.
Hu Z, Abramoff MD, Kwon YH, Lee K, Garvin MK: Automated segmentation of neural canal opening and optic cup in 3D spectral optical coherence tomography images of the optic nerve head . Invest Ophthalmol Vis Sci. 2010, 51 (11): 5708-5717.PubMedPubMedCentral
50.
Li H, Lim J, Liu J, Mitchell P, Tan A, Wang J, Wong T: A computer-aided diagnosis system of nuclear cataract . IEEE Trans Biomed Eng. 2010, 57 (7): 1690-1698.PubMed
51.
Duncan D, Shukla O, West S, Schein O: New objective classification system for nuclear opacification . J Optical Soc Am A, Optics Image Sci Vis. 1997, 14 (6): 1197-1204.
52.
Fan S, Dyer C, Hubbard L, Klein B: An automatic system for classification of nuclear sclerosis from slit-lamp photographs . Proceedings Int Conf MICCAI, Lecture Notes in Computer Science. 2003, Heidelberg: Springer Berlin, 592-601.
53.
Nidek Co. Ltd: Anterior eye segment analysis system: EAS-1000. Operator’s Manual, Nidek, Japan . 1991,
54.
Gershenzon A, Robman L: New software for lens retro-illumination digital image analysis . Aust N Z J Ophthalmol. 1999, 27 (3–4): 170-172.PubMed
55.
Klein B, Klein R, Linton K, Magli Y, Neider M: Assessment of cataracts from photographs in the Beaver Dam Eye Study . Ophthalmology. 1990, 97 (11): 1428-1433.PubMed
56.
Gao X, Li H, Lim JH, Wong TY: Computer-aided cataract detection using enhanced texture features on retro-illumination lens images . Proceedings of IEEE Int. Conf. Image Processing. 2011, IEEE, 1565-1568.
57.
Chow YC, Gao X, Li H, Lim JH, Sun Y, Wong TY: Automatic detection of cortical and PSC cataracts using texture and intensity analysis on retro-illumination lens images . Conf Proceedings of IEEE Eng Med Biol Soc. 2011, IEEE, 5044-5047.
58.
Gao X, Wong DWK, Ng TT, Cheung CYL, Cheng CY, Wong TY: Automatic grading of cortical and PSC cataracts using retroillumination lens images . Proceedings of the 11th Asian conference on Computer Vision-Volume Part II. 2012, Heidelberg: Springer Berlin, 256-267.
59.
Sehi M, Guaqueta D, Feuer W, Greenfield D: Scanning laser polarimetry with variable and enhanced corneal compensation in normal and glaucomatous eyes . Am J Ophthalmol. 2007, 143 (2): 272-279.PubMed
60.
Lee PJ, Liu CJ, Wojciechowski R, Bailey-Wilson JE, Cheng CY: Structure-function correlations using scanning laser polarimetry in primary angle-closure glaucoma and primary open-angle glaucoma . Am J Ophthalmol. 2010, 149 (5): 817-825.PubMedPubMedCentral
61.
Vermeer K, Lo B, Zhou Q, Vos F, Vossepoel A, Lemij H: Event-based progression detection strategies using scanning laser polarimetry images of the human retina . Comput Biol Med. 2011, 41 (9): 857-864.PubMed
62.
Medeiros F, Zangwill L, Bowd C, Weinreb R: Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and stratus OCT optical coherence tomograph for the detection of glaucoma . Arch Ophthalmol. 2004, 122 (6): 827-837.PubMed
63.
Ben Sbeh Z, Cohen LD, Mimoun G, Coscas G: A new approach of geodesic reconstruction for drusen segmentation in eye fundus images . IEEE Trans Med Imaging. 2001, 20 (12): 1321-1333.PubMed
64.
Karnowski TP, Govindasamy VP, Tobin KW, Chaum E, Abramoff M: Retina lesion and microaneurysm segmentation using morphological reconstruction methods with ground-truth data . Conf Proceedings of IEEE Eng Med Biol Soc. 2008, IEEE, 5433-5436.
65.
Rapantzikos K, Zervakis M, Balas K: Detection and segmentation of drusen deposits on human retina: Potential in the diagnosis of age-related macular degeneration . Med Image Anal. 2003, 7: 95-108.PubMed
66.
Hoover A, Kouznetsoza V, Goldbaum M: Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response . IEEE Trans Med Imag. 2000, 19 (3): 203-210.
67.
Lowell J, Hunter A, Steel D, Basu A, Ryder R, Kennedy L: Measurement of retinal vessel widths from fundus images based on 2-D modeling . IEEE Trans Biomed Eng. 2004, 23 (10): 1196-1204.
68.
Heneghan C, Flynn J, OKeef M, Cahill M: Characterization of changes in blood vessel and tortuosity in retinopathy of prematurity using image analysis . Med Image Anal. 2002, 6 (4): 407-429.PubMed
69.
Joshi G, Sivaswamy J, Krishnadas S: Optic disk and cup segmentation from monocular color retinal images for glaucoma assessment . IEEE Tran Med Imaging. 2011, 30 (6): 1192-1205.
70.
Hatanaka Y, Noudo A, Muramatsu C, Sawada A, Hara T, Yamamoto T, Fujita H: Automatic measurement of vertical cup-to-disc ratio on retinal fundus images . Medi Biometrics, Lect Notes Comput Sci. 2010, 6165: 64-72.
71.
Liu J, Wong DWK, Lim JH, Tan NM, Zhang Z, Li H, Yin F, Lee BH, Saw SM, Louis T, W TY: Detection of pathological myopia by PAMELA with texture-based features through an SVM approach . J Healthcare Eng. 2010, 1 (1): 1-12.
72.
Tan NM, Liu J, Wong DWK, Lim JH, Zhang Z, Lu S, Li H, Saw SM, Wong TY: Automatic detection of pathological myopia using variational level set . Conf Proceedings IEEE Eng Med Biol Soc. 2009, IEEE, 3609-3612.
73.
Cheng J, Tao D, Liu J, Wong DWK, Tan NM, Wong TY, Saw SM: Peripapillary atrophy detection by sparse biologically inspired feature manifold . IEEE Trans Med Imaging. 2012, 31 (12): 2355-2365.PubMed
74.
Smith RT, Chan JK, Nagasaki T, Ahmad UF, Barbazetto I, Sparrow J, Figueroa M, Merriam J: Automated detection of macular drusen using geometric background leveling and threshold selection . Arch Ophthalmol. 2005, 123 (2): 200-206.PubMedPubMedCentral
75.
Lee B, Adam H: Drusen detection in a retinal image using multi-level analysis . Proceedings of Int Conf MICCAI. 2003, Heidelberg: Springer Berlin, 618-625.
76.
Freund D, Bressler N, Burlina P: Automated detection of drusen in the macula . Proceedings of IEEE Int Symposium Biomedical Imaging. 2009, IEEE, 61-64.
77.
Tamura S, Okamoto Y, Yanashima K: Zero-crossing interval correction in tracing eye-fundus blood vessels . Pattern Recogn. 1988, 21 (3): 227-233.
78.
Kochner B, Schulmann D, Michaelis M, Mann G, Englemeier K: Course tracking and contour extraction of retinal vessels from colour fundus photographs: most efficient use of steerable filters for model based image analysis . Proceedings of SPIE Conference on Medical Imaging. 1988, Bellingham: International Society for Optics and Photonics, 755-761.
79.
Antal B, Hajdu A: An ensemble-based system for microaneurysm detection and diabetic retinopathy grading . IEEE Trans Biomed Eng. 2012, 59 (6): 1720-1726.PubMed
80.
Wong DWK, Liu J, Lim JH, Jia X, Yin F, Li H, Wong TY: Level-set based automatic cup-to-disc ratio determination using retinal fundus images in ARGALI . Proceedings 30th Annual Intl conf. of the IEEE Eng Med Biol Soc. 2008, IEEE, 2266-2269.
81.
Bock R, Meier J, Michelson G, Nyl L, Hornegger J: Classifying glaucoma with image-based features from fundus photographs . Lect Notes Comput Sci. 2007, 4713: 355-364.
82.
Meier J, Bock R, Michelson G, Nyl LG, Hornegger J: Effects of preprocessing eye fundus images on appearance based glaucoma classification . Lect Notes Comput Sci. 2007, 4673: 165-172.
83.
Liu J, Wong D, Tan N, Zhang Z, Lu S, Lim J, Li H, Saw S, Tong L, Wong T: Automatic classification of pathological myopia in retinal fundus images using PAMELA . Proceedings of SPIE Conference on Medical Imaging. 2010, Bellingham: International Society for Optics and Photonics, 76240G-76240G.
84.
Barriga E, Murray V, Agurto C, Pattichis M, Russell S, Abramoff M, Davis H, Soliz P: Multi-scale AM-FM for lesion phenotyping on age-related macular degeneration . Proceedings IEEE Int Symp Computer-Based Medical Systems. 2009, IEEE, 1-5.
85.
Soliz P, Russell SR, Abramoff MD, Murillo S, Pattichis M, Davis H: Independent component analysis for vision-inspired classification of retinal images with age-related macular degeneration . Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation. 2008, IEEE, 65-68.
86.
Zheng Y, Vanderbeek B, Daniel E, Stambolian D, Maguire M, Brainard D, Gee J: An automated drusen detection system for classifying age-related maculardegeneration with color fundus photographs . Proceedings on IEEE International Symposium on Biomedical Imaging. 2013, IEEE, 1440-1443.
87.
Harangi B, Lazar I, Hajdu A: Automatic exudate detection using active contour model and regionwise classification . Conf Proceedings of IEEE Eng Med Biol Soc. 2012, IEEE, 5951-4.
88.
Martins CIO, Medeiros F, Veras RM, Bezerra FN, Cesar R: Evaluation of retinal vessel segmentation methods for microaneurysms detection . Proceedings of IEEE Int. Conf. Image Processing. 2009, IEEE,
89.
Jaafar HF, Nandi AK, Al-Nuaimy W: Detection of exudates in retinal images using a pure splitting technique . Conf Proceedings of IEEE Eng Med Biol Soc. 2010, IEEE,
90.
Bock R, Meier J, Nyl L, Michelson G: Glaucoma risk index: Automated glaucoma detection from color fundus images . Med Image Anal. 2010, 14: 471-481.PubMed
91.
Cheng J, Tao D, Liu J, Wong D, Lee B, Mani B, Wong T, Aung T: Focal Biologically Inspired Feature for Glaucoma Type Classification . Proceedings of Int Conf MICCAI. 2011, Heidelberg: Springer Berlin, 91-98.
92.
Xu Y, Liu J, Lin S, Xu D, Cheung C, Aung T, Wong T: Efficient optic cup detection from intra-image learning with retinal structure priors . Proceedings Int Conf MICCAI. 2012, Heidelberg: Springer Berlin, 58-65.
93.
Cheng J, Wong DWK, Cheng X, Liu J, Tan NM, Bhargava M, Cheung CMG, Wong TY: Early age-related macular degeneration detection by focal biologically inspired feature . Proceedings of IEEE Int. Conf. Image Processing. 2012, IEEE, 2805-2808.
94.
Köse C, Sevik U, Gencalioglu O, Ikibas C, Kayikicioglu T: A statistical segmentation method for measuring age-related macular degeneration in retinal fundus images . J Med Sys. 2010, 34: 1-13.
95.
Quellec G, Russell SR, Abràmoff MD: Optimal filter framework for automated, instantaneous detection of lesions in retinal images . IEEE Trans Med Imaging. 2011, 30 (2): 523-533.PubMed
96.
Walter T, Massin P, Erginay A, Ordonez R, Jeulin C, Klein JC: Automatic detection of microaneurysms in color fundus images . Med Image Anal. 2007, 11 (6): 555-566.PubMed
97.
Lazar I, Hajdu A: Retinal microaneurysm detection through local rotating cross-section profile analysis . IEEE Trans Med Imaging. 2013, 32 (2): 400-407.PubMed
98.
Fleming AD, Philip S, Goatman KA, Olson JA, Sharp PF: Automated microaneurysm detection using local contrast normalization and local vessel detection . IEEE Trans Med Imaging. 2006, 25 (9): 1223-1232.PubMed
99.
Ohwada H, Daidoji M, Shirato S, Mizoguchi F: Learning first order rules from image applied to glaucoma diagnosis . Proceedings of Pacific Rim International Conference on Artificial Intelligence. 1998, Heidelberg: Springer Berlin, 494-505.
100.
Nyul LG: Retinal image analysis for automated glaucoma risk evaluation . Proceedings of SPIE Conference on Medical Imaging. 2009, Bellingham: International Society for Optics and Photonics, 74971C1-9.
101.
McIntyre R, Heywood MI, Artes PH, Abidi SSR: Toward glaucoma classification with moment methods . Proceedings First Canadian Conference on Computer and Robot Vision. 2004, IEEE, 265-272.
102.
Ujjwal K, Chakravarty A, Sivaswamy J: Visual saliency based bright lesion detection and discrimination in retinal images . Proceedings IEEE 10th Int Symposium Biomedical Imaging: From Nano to Macro. 2013, IEEE, 1428-1431.
103.
Medhi JP, Nath MK, Dandapat S: Automatic grading of macular degeneration from color fundus images . Proceedings of World Congress on Information and Communication Technologies. 2012, IEEE, 511-514.
104.
Liang Z, Wong DW, Liu J, Chan KL, Wong TY: Towards automatic detection of age-related macular degeneration in retinal fundus images . Conf Proceedings of IEEE Eng Med Biol Soc. 2010, IEEE, 4100-4103.
105.
Esmaeili M, Rabbani H, Dehnavi AM, Dehghani A: A new curvelet transform based method for extraction of red lesions in digital color retinal images . Proceedings of IEEE Int. Conf. Image Processing. 2010, IEEE,
106.
Ravishankar S, Jain A, Mittal A: Automated feature extraction for early detection of diabetic retinopathy in fundus images . Proceedings IEEE Conf. on Comp Vis Pattern Recognition. 2009, IEEE,
107.
Antal B, Hajdu A: Improving microaneurysm detection using an optimally selected subset of candidate extractors and preprocessing methods . Pattern Recognition. 2012, 45: 264-270.
108.
Yu J, Abidi SSR, Artes PH, Mcintyre A, Heywood M: Automated optic nerve analysis for diagnostic support in glaucoma . Proceedings of IEEE Symposium on Computer-Based Medical Systems. 2005, IEEE, 97-102.
109.
Xu Y, Lin S, Wong DWK, Liu J, Xu D: Efficient reconstruction-based optic cup localization for glaucoma screening . Proceedings of Int Conf MICCAI. 2013, Springer Berlin: Heidelberg, 445-452.
110.
Muramatsu C, Nakagawa T, Sawada A, Hatanaka Y, Hara T, Yamamoto T, Fujita H: Determination of cup and disc ratio of optical nerve head for diagnosis of glaucoma on stereo retinal fundus image pairs . Proceedings of SPIE Conference on Medical Imaging. 2009, Bellingham: International Society for Optics and Photonics, 603-610.
111.
Hijazi MHA, Coenen F, Zheng Y: Retinal image classification using a histogram based approach . IEEE International Joint Conference on Neural Networks. 2010, IEEE, 3501-3507.
112.
Ahmad HMH, Frans C, Yalin Z: Retinal image classification for the screening of age-related macular degeneration . Research and Development in Intelligent Systems XXVII. 2011, London: Springer,
113.
Zuiderveld K: Contrast limited adaptive histogram equalization . Graphics gems IV. 1994, San Diego, CA, USA: Academic Press Professional, Inc., 474-485.
114.
Lay B, Baudoin C, Klein JC: Automatic detection of microaneurysms in retinopathy fluoro-angiogram . Proceedings of 27th Annual Techincal Symposium. 1984, Bellingham: International Society for Optics and Photonics, 165-173.
115.
Cree MJ, Olson JA, McHardy KC, Sharp PF, Forrester JV: A fully automated comparative microaneurysm digital detection system . Eye. 1997, 11 (5): 622-628.PubMed
116.
Cheng J, Liu J, Tao D, Yin F, Wong D, Wong TY: Superpixel classification based optic cup segmentation . Proceedings of Int Conf MICCAI. 2013, Heidelberg: Springer Berlin, 421-428.
117.
Cheng J, Liu J, Xu Y, Yin F, Wong DWK, Tan NM, Tao D, Cheng CY, Aung T, Wong TY: Superpixel classification based optic disc and optic cup segmentation for glaucoma screening . IEEE Trans Med Imaging. 2013, 32 (6): 1019-1032.PubMed
118.
Xu Y, Xu D, Lin S, Liu J, Cheng J, Cheung CY, Aung T, Wong TY: Sliding window and regression based cup detection in digital fundus images for glaucoma diagnosis . Proceedings Int Conf MICCAI. 2011, Heidelberg: Springer Berlin, 1-8.
119.
Ahmad HMH, Chuntao J, Frans C, Yalin Z: Image classification for age-related macular degeneration screening using hierarchical image decompositions and graph mining . Lect Notes Comput Sci. 2011, 6912: 65-80.
120.
Zheng Y, Hijazi MHA, Coenen F: Automated “disease/no disease” grading of age-related macular degeneration by an image mining approach . Invest Ophthalmol Vis Sci. 2012, 53 (13): 8310-8318.PubMed
121.
Priya R, Aruna P: Automated diagnosis of Age-related macular degeneration from color retinal fundus images . Proceedings of the 3rd International Conference on Electronics Computer Technology. 2011, IEEE, 227-230.
122.
Walter T, Klein JC: Automatic detection of microaneurysms in color fundus images of the human retina by means of the bounding box closing . Proceedings the Third International Symposium on Medical Data Analysis. 2002, Heidelberg: Springer Berlin, 210-220.
123.
Niemeijer M, van Ginneken B, Staal J, Suttorp-Schulten MS, Abràmoff MD: Automatic detection of red lesions in digital color fundus photographs . IEEE Trans Med Imaging. 2005, 24 (5): 584-592.PubMed
124.
Sinthanayothin C, Boyce J, Williamson T, Cook H, Mensah E, Lal S, Usher D: Automated detection of diabetic retinopathy on digital fundus images . Diabet Med. 2002, 19 (2): 105-112.PubMed
125.
Wong D, Liu J, Lim JH, Li H, Jia X, Yin F, Wong TY: Automated detection of kinks from blood vessels for optic cup segmentation in retinal images . Proceedings of SPIE Conference on Medical Imaging. 2009, Bellingham: International Society for Optics and Photonics, 72603L1-8.
126.
Joshi GD, Sivaswamy J, Karan K, Prashanth R, Krishnadas R: Vessel bend-based cup segmentation in retinal images . Proceedings of Int. Conf. Pattern Recognition, Istanbul, Turkey. 2010, IEEE, 2536-2539.
127.
Chaum E, Karnowski TP, Govindasamy VP, Abdelrahman M, Tobin KW: Automated diagnosis of retinopathy by content-based image retrieval . Retina. 2008, 28 (10): 1463-1477.PubMed
128.
Tobin KW, Abdelrahman M, Chaum E, Govindasamy VP, Karnowski TP: A probabilistic framework for content-based diagnosis of retinal disease . Conf Proceedings IEEE Eng Med Biol Soc, Lyon, France. 2007, IEEE, 6743-6746.
129.
Gardner G, Keating D, Williamson T, Elliott A: Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool . Br J Ophthalmol. 1996, 80 (11): 940-944.PubMedPubMedCentral
130.
Akram MU, Khalid S, Khan SA: Identification and classification of microaneurysms for early detection of diabetic retinopathy . Pattern Recognit. 2013, 46: 107-116.
131.
Zhang B, Karray F, Zhang L, You J: Microaneurysm (MA) detection via sparse representation classifier with MA and Non-MA dictionary learning . Proceedings Int Conf Pattern Recognition: Istanbul, Turkey. 2010, IEEE, 277-280.
132.
Xu J, Chutatape O, Sung E, Zheng C, Kuan P: Optic disc feature extraction via modified deformable model technique for glaucoma analysis . Pattern Recognit. 2007, 40 (7): 2063-2076.
133.
Abramoff M, Alward W, Greenlee E, Shuba L, Kim C, Fingert J, Kwon Y: Automated Segmentation of the optic disc from stereo color photographs using physiologically plausible features . Invest Ophthalmol Vis Sci. 2007, 48 (4): 1665-PubMedPubMedCentral
134.
Corona E, Mitra S, Wilson M, Krile T, Kwon YH, Soliz P: Digital stereo image analyzer for generating automated 3D measures of optic disc deformation in glaucoma . IEEE Trans Med Imag. 2002, 21 (10): 1244-1253.
135.
Niemeijer M, van Ginneken B, Russell SR, Suttorp-Schulten MS, Abramoff MD: Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis . Invest Ophthalmol Vis Sci. 2007, 48 (5): 2260-2267.PubMedPubMedCentral
136.
Mubbashar M, Usman A, Akram MU: Automated system for macula detection in digital retinal images . Proceedings of Int. Conf. on Information and Communication Technologies, Karachi, Pakistan. 2011, IEEE, 1-5.
137.
Hunter A, Lowell JA, Ryder B, Basu A, Steel D: Automated diagnosis of referable maculopathy in diabetic retinopathy screening . Conf Proceedings of IEEE Eng Med Biol Soc, Boston. 2011, IEEE, 3375-3378.
138.
Ram K, Joshi GD, Sivaswamy J: A successive clutter-rejection-based approach for early detection of diabetic retinopathy . IEEE Trans Biomed Eng. 2011, 58 (3): 664-673.PubMed
139.
Zhang B, Wu X, You J, Li Q, Karray F: Detection of microaneurysms using multi-scale correlation coefficients . Pattern Recognit. 2010, 43 (6): 2237-2248.
140.
Guesalag A, Irarrźabal P, Guarini M, Álvarez R: Measurement of the glaucomatous cup using sequentially acquired stereoscopic images . Measurement. 2003, 34 (3): 207-213.
141.
Merickel MB, Wu X, Sonka M, Abramoff M: Optimal segmentation of the optic nerve head from stereo retinal images . Proceedings of SPIE Conference on Medical Imaging, San Diego, California, United States. 2006, Bellingham: International Society for Optics and Photonics, 1031-1038.
142.
Lu S, Liu J, Lim JH, Zhang Z, Meng TN, Wong WK, Li H, Wong TY: Automatic fundus image classification for computer-aided diagonsis . Conf Proceedings of IEEE Eng Med Biol Soc, Minnesota, USA. 2009, IEEE, 1453-1456.
143.
Cheng X, Wong DWK, Liu J, Lee BH, Tan NM, Zhang J, Cheng CY, Cheung G, Wong TY: Automatic localization of retinal landmarks . Conf Proceedings of IEEE Eng Med Biol Soc, San Diego, California, USA. 2012, IEEE, 4954-4957.
144.
Lee N, Wielaard J, Fawzi A, Sajda P, Laine A, Martin G, Humayun M, Smith R: In vivo snapshot hyperspectral image analysis of age-related macular degeneration . Conf Proceedings of IEEE Eng Med Biol Soc, Istanbul, Turkey. 2010, IEEE, 5363-5366.
145.
Jaafar HF, Nandi AK, Al-Nuaimy W: Automated detection of red lesions from digital colour fundus photographs . Conf Proceedings of IEEE Eng Med Biol Soc, Boston. 2011, IEEE, 584-592.
146.
Agurto C, Murray V, Barriga E, Murillo S, Pattichis M, Davis H, Russell S, Abràmoff M, Soliz P: Multiscale AM-FM methods for diabetic retinopathy lesion detection . IEEE Trans Med Imaging. 29 (2): 502-512.
147.
Jain N, Farsiu S, Khanifar AA, Bearelly S, Smith RT, Izatt JA, Toth CA: Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs . Invest Ophthalmol Vis Sci. 2010, 51 (10): 4875-4883.PubMedPubMedCentral
148.
Niemeijer M, van Ginneken B, Russell SR, Suttorp-Schulten MS, Abramoff MD: Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis . Invest Ophthalmol Vis Sci. 2007, 48 (5): 2260-2267.PubMedPubMedCentral
149.
Jelinek HF, Rocha A, Carvalho T, Goldenstein S, Wainer J: Machine learning and pattern classification in identification of indigenous retinal pathology . Conf Proceedings of IEEE Eng Med Biol Soc, Boston. 2011, IEEE, 5951-5954.
150.
Tang L, Niemeijer M, Reinhardt J, Garvin M, Abramoff M: Splat feature classification with application to retinal hemorrhage detection in fundus images . IEEE Trans Med Imaging. 2013, 32 (2): 364-375.PubMed
151.
Hani AFM, Ngah NF, George TM, Izhar LI, Nugroho H, Nugroho HA: Analysis of foveal avascular zone in colour fundus images for grading of diabetic retinopathy severity . Conf Proceedings of IEEE Eng Med Biol Soc, Buenos Aires. 2010, IEEE, 5632-5635.
152.
Oloumi F, Rangayyan RM, Ells AL: Computer-aided diagnosis of proliferative diabetic retinopathy . Conf Proceedings IEEE Eng Med Biol Soc, San Diego, California, USA. 2012, IEEE, 1438-1441.
153.
Niemeijer M, Abramoff MD, van Ginneken B: Information fusion for diabetic retinopathy CAD in digital color fundus photographs . IEEE Trans Med Imaging. 2009, 28 (5): 775-785.PubMed
154.
Rocha A, Carvalho T, Jelinek HF, Goldenstein S, Wainer J: Points of interest and visual dictionaries for automatic retinal lesion detection . IEEE Trans Biomed Eng. 2012, 59 (8): 2244-2253.PubMed
155.
Abràmoff MD, Folk JC, Han DP, Walker JD, Williams DF, Russell SR, Massin P, Cochener B, Gain P, Tang L, Lamard M, Moga DC, Quellec G, Niemeijer M: Automated analysis of retinal images for detection of referable diabetic retinopathy . JAMA Ophthalmology. 2013, 131 (3): 351-357.PubMed
156.
Murray V, Agurto C, Barriga S, Pattichis MS, Soliz P: Real-time diabetic retinopathy patient screening using multiscale AM-FM methods . Proceedings of IEEE Int. Conf. Image Processing, Orlando, Florida, USA. 2012, IEEE, 525-528.
157.
Agurto C, Barriga ES, Murray V, Nemeth S, Crammer R, Bauman W, Zamora G, Pattichis MS, Soliz P: Automatic detection of diabetic retinopathy and age-related macular degeneration in digital fundus images . Invest Ophthalmol Vis Sci. 2011, 52 (8): 5862-5871.PubMedPubMedCentral
158.
Quellec G, Lamard M, Josselin PM, Cazuguel G, Cochener B, Roux C: Optimal wavelet transform for the detection of microaneurysms in retina photographs . IEEE Trans Med Imaging. 2008, 27 (9): 1230-1241.PubMedPubMedCentral
159.
Burgansky-Eliash Z, Wollstein G, Bilonick R, Ishikawa H, Kagemann L, Schuman J: Glaucoma detection with the Heidelberg Retina Tomograph 3 . Ophthalmology. 2007, 114 (3): 466-471.PubMed
160.
Chauhan B, Blanchard J, Hamilton D, LeBlanc R: Technique for detecting serial topographic changes in the optic disc and peripapillary retina using scanning laser tomography . Invest Ophthalmol Vis Sci. 2000, 41 (3): 775-782.PubMed
161.
Miglior S, Guareschi M, Albe E, Gomarasca S, Vavassori M, Orzalesi N: Detection of glaucomatous visual field changes using the Moorfields regression analysis of the Heidelberg retina tomograph . Am J Ophthalmol. 2003, 136: 26-33.PubMed
162.
Wollstein G, Garway-Heath D, Hitchings R: Identification of early glaucoma cases with the scanning laser ophthalmoscope . Ophthalmology. 1998, 105 (8): 1557-1563.PubMed
163.
Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, Hee MR, Flotte T, Gregory K, Puliafito CA: Optical coherence tomography . Science. 1991, 254 (5035): 1178-1181.PubMedPubMedCentral
164.
Hee MR, Baumal CR, Puliafito CA, Duker JS, Reichel E, Wilkins JR, Coker JG, Schuman JS, Swanson EA, Fujimoto JG: Optical coherence tomography of age-related macular degeneration and choroidal neovascularization . Ophthalmology. 1996, 103 (8): 1260-PubMed
165.
Fujimoto JG: Optical coherence tomography for ultrahigh resolution in vivo imaging . Nat Biotechnol. 2003, 21 (11): 1361-1367.PubMed
166.
Pardianto G: Understanding diabetic retinopathy . Mimbar Ilmiah Oftalmologi Indonesia. 2005, 2: 65-6.
167.
Jelinek HJ, Cree MJ, Worsley D, Luckie A, Nixon P: An automated microaneurysm detector as a tool for identification of diabetic retinopathy in rural optometric practice . Clin Exp Optomet. 2006, 89 (5): 299-305.
168.
Michelson G, Wrntges S, Hornegger J, Lausen B: The papilla as screening parameter for early diagnosis of glaucoma . Deutsches Aerzteblatt Int. 2008, 105: 34-35.
169.
Mookiah M, Acharya U, Lim CM, Petznick A, S Suri J: Data mining technique for automated diagnosis of glaucoma using higher order spectra and wavelet energy features . Knowledge-Based Syst. 2012, 33: 73-82.
170.
Damms T, Dannheim F: Sensitivity and specificity of optic disc parameters in chronic glaucoma . Invest Ophth Vis Sci. 1993, 34 (7): 2246-2250.
171.
Michael D, Hancox OD: Optic disc size, an important consideration in the glaucoma evaluation . Clin Eye Vis Care. 1999, 11 (2): 59-62.
172.
Mookiah M, Acharya U, Chua C, Min L, Ng E, Mushrif M, Laude A: Automated detection of optic disk in retinal fundus images using intuitionistic fuzzy histon segmentation . Proc Inst Mech Eng H. 2013, 227 (1): 37-49.PubMed
173.
Harizman N, Oliveira C, Chiang A, Tello C, Marmor M, Ritch R, Liebmann JM: The ISNT rule and differentiation of normal from glaucomatous eyes . Arch Ophthalmol. 2006, 124 (11): 1579-1583.PubMed
174.
Jonas J, Fernandez M, Naumann G: Glaucomatous parapapillary atrophy: Occurrence and correlations . Arch Ophthalmol. 1992, 110: 214-222.PubMed
175.
Allingham R: Shields’ Textbook of Glaucoma. 2004, Philadelphia, USA: Lippincott Williams & Wilkins
176.
Bressler NM, Bressler SB, Fine SL: Age-related macular degeneration . Surv Ophthalmol. 1988, 32 (6): 375-413.PubMed
177.
De J, Paulus T: Age-related macular degeneration . N Engl J Med. 2006, 355 (14): 1474-1485.
178.
Hijazi MHA, Coenen F, Zheng Y: Data mining techniques for the screening of age-related macular degeneration . Knowledge-Based Syst. 2012, 29: 83-92.
179.
Saw S, Katz J, Schein O, Chew S, Chan T: Epidemiology of myopia . Epidemiol Rev. 1996, 18 (2): 175-187.PubMed
180.
Young T, Ronan S, Alvear A, Wildenberg S, Oetting W, Atwood L, Wilkin D, King R: A second locus for familial high myopia maps to chromosome 12q . Am J Hum Genet. 1998, 63 (5): 1419-24.PubMedPubMedCentral
181.
Xu Y, Liu J, Zhang Z, Tan NM, Wong D, Saw SM, Wong TY: Learn to recognize pathological myopia in fundus images using bag-of-feature and sparse learning approach . Proceedings IEEE 10th Int Symposium Biomedical Imaging, San Francisco, USA. 2013, IEEE, 888-891.
182.
Cheng J, Tao D, Liu J, Wong D, Tan N, Wong T, Saw S: Peripapillary atrophy detection by sparse biologically inspired feature manifold . IEEE Trans Med Imaging. 2012, 31 (12): 2355-2365.PubMed
183.
Lim L, Cheung G, Lee S: Comparison of spectral domain and swept-source optical coherence tomography in pathological myopia . Eye (Lond). 2014, 28 (4): 488-491.
184.
185.
Varma R, Steinmann W, Spaeth G, Wilson R: Variability in digital analysis of optic disc topography . Graefes Arch Clin Exp Ophthalmol. 1988, 226 (5): 435-42.PubMed
186.
Jonas J, Martus P, Budde W, Hayler J: Morphologic predictive factors for development of optic disc hemorrhages in glaucoma . Invest Ophthalmol Vis Sci. 2002, 43 (9): 2956-2961.PubMed
187.
Lowell J, Hunter A, Steel D, Basu A, Ryder R, Fletcher R, Kennedy L: Optic nerve head segmentation . IEEE Trans Med Imaging. 2004, 23 (2): 256-264.PubMed
188.
Wong D, Liu J, Tan N, Yin F, Wong T: Automatic detection of the optic cup using vessel kinking in digital retinal fundus images . Proceedings IEEE Int Symposium Biomedical Imaging, Barcelona, Spain. 2012, IEEE, 1647-1650.
189.
Joshi G, Sivaswamy J, Krishnadas S: Depth discontinuity-based cup segmentation from multiview color retinal image . IEEE Trans Biomed Eng. 2012, 59 (6): 1523-1531.PubMed
190.
Cheng J, Liu J, Wong DWK, Tan NM, Cheung C, Baskaran M, Wong TY, Saw SM: Peripapillary atrophy detection by biologically inspired feature . Proceedings of Int Conf Pattern Recognition, Tsukuba, Japan. 2012, IEEE, 2063-2066.
191.
Wang Y, Shen J, Liao W, Zhou L: Automatic fundus images mosaic based on SIFT feature . Proceedings the 3rd International Congress on Image and Signal Processing, Yantai, China. 2010, IEEE, 2747-2751.
192.
Lowe D: Distinctive image features from scale-invariant keypoints . Int J Comput Vis. 2004, 60 (2): 91-110.
193.
Ren X, Malik J: Learning a classification model for segmentation . Proceedings Int Conf Computer Vision, Nice, France. 2003, IEEE, 10-17.
194.
Mori G, Ren X, Efros A, Malik J: Recovering human body configurations: combining segmentation and recognition . Proceedings IEEE Conf Computer Vision and Pattern Recognition, Washington. 2004, IEEE,
195.
Radhakrishna A, Shaji A, Smith K, Lucchi A, Fua P, Susstrunk S: Slic superpixels . Technical Report 149300, EPFL. 2010,
196.
Caruana R: Multitask learning . Mach Learn. 1997, 28: 41-75.
197.
Thrun S: Is learning the n-th thing any easier than learning the first? . Adv Neural Inform Process Syst MIT Press. 1996, 8: 640-646.
198.
Mihalkova L, Huynh T, Mooney R: Mapping and Revising Markov Logic Networks for Transfer Learning . Proceedings the 22nd AAAI Conference on Artificial Intelligence, Vancouver, Canada. 2007, California: AAAI, 608-614.
199.
Holtzman NA, Murphy PD, Watson MS, Barr PA: Predictive genetic testing: from basic research to clinical practice . Science. 1997, 278 (5338): 602-605.PubMed
200.
Sanfilippo P, Hewitt A, Hammond C, Mackey D: The heritability of ocular traits . Surv Ophthalmol. 2010, 55 (6): 561-583.PubMed
201.
Plomin R, DeFries J, McClearn G: Behavioral Genetics. 2001, New York: World Publishers
202.
Herskind AM, McGue M, Holm NV, Sörensen TI, Harvald B, Vaupel JW: The heritability of human longevity: a population-based study of 2872 Danish twin pairs born 1870-1900 . Hum Genet. 1996, 97 (3): 319-323.PubMed
203.
Karasik D, Demissie S, Cupples LA, Kiel DP: Disentangling the genetic determinants of human aging: biological age as an alternative to the use of survival measures . J Gerontol Ser A: Biol Sci Med Sci. 2005, 60 (5): 574-587.
204.
Schnoll R, Johnson T, Lerman C: Genetics and smoking behavior . Curr Psychiat Rep. 2007, 9 (5): 349-57.
205.
Vink J, Willemsen G, Boomsma D: Heritability of smoking initiation and nicotine dependence . Behav Genet. 2005, 35 (4): 397-406.PubMed
206.
Jablonski W: A contribution to the heredity of refraction in human eyes . Arch Augenheilk. 1922, 91: 308-28.
207.
Fajnkuchen F, Cohen S: Update on the genetics of age-related macular degeneration . Fr J Ophtalmol. 2008, 31 (6 Pt 1): 630-637.
208.
Antoniak K, Bienias W, Nowak J: Age-related macular degeneration-a complex genetic disease . Klin Oczna. 2008, 110 (4–6): 211-218.PubMed
209.
Scholl H, Fleckenstein M, Charbel IP, Keilhauer C, Holz F, Weber B: An update on the genetics of age-related macular degeneration . Mol Vis. 2007, 7 (13): 196-205.
210.
Seddon J, Cote J, Page W, Aggen S, Neale M: The US twin study of age-related macular degeneration: relative roles of genetic and environmental influences . Arch Ophthalmol. 2005, 123 (3): 321-327.PubMed
211.
Hammond C, Webster A, Snieder H, Bird A, Gilbert C, Spector T: Genetic influence on early age-related maculopathy: a twin study . Ophthalmology. 2002, 109 (4): 730-736.PubMed
212.
Munch IC, Sander B, Kessel L, Hougaard JL, Taarnhoj NCBB, Sorensen TI, Kyvik KO, Larsen M: Heredity of small hard drusen in twins aged 20-46 years . Invest Ophthalmol Vis Sci. 2007, 48 (2): 833-838.PubMed
213.
Toh T, Liew S, MacKinnon J, Hewitt A, Poulsen J, Spector T, Gilbert C, Craig J, Hammond C, Mackey D: Central corneal thickness is highly heritable: the twin eye studies . Invest Ophthalmol Vis Sci. 2005, 46 (10): 3718-22.PubMed
214.
Charlesworth J, Kramer P, Dyer T, Diego V, Samples J, Craig J, Mackey D, Hewitt A, Blangero J, Wirtz M: The path to open-angle glaucoma gene discovery: endophenotypic status of intraocular pressure, cup-to-disc ratio, and central corneal thickness . Invest Ophthalmol Vis Sci. 2010, 51 (7): 3509-3514.PubMedPubMedCentral
215.
Klein B, Klein R, Lee K: Heritability of risk factors for primary open-angle glaucoma: the Beaver Dam Eye Study . Invest Ophthalmol Vis Sci. 2004, 45 (1): 59-62.PubMed
216.
Dirani M, Islam A, Shekar S, Baird P: Dominant genetic effects on corneal astigmatism: the genes in myopia (GEM) twin study . Invest Ophthalmol Vis Sci. 2008, 49 (4): 1339-1344.PubMed
217.
Congdon N, Broman K, Lai H, Munoz B, Bowie H, Gilbert D, Wojciechowski R, West S: Cortical, but not posterior subcapsular, cataract shows significant familial aggregation in an older population after adjustment for possible shared environmental factors . Ophthalmology. 2005, 112: 73-77.PubMedPubMedCentral
218.
Hammond C, Duncan D, Snieder H, de Lange M, West S, Spector T, Gilbert C: The heritability of age-related cortical cataract: the twin eye study . Invest Ophthalmol Vis Sci. 2001, 42 (3): 601-5.PubMed
219.
Teikari J: Genetic factors in open-angle (simple and capsular) glaucoma. A population-based twin study . Acta Ophthalmol. 1987, 65 (6): 715-720.
220.
Alsbirk P: Anterior chamber depth and primary angle-closure glaucoma. II. A genetic study . Acta Ophthalmol. 1975, 53 (3): 436-449.
221.
Tu Y, Yin Z, Pen H, Yuan C: Genetic heritability of a shallow anterior chamber in Chinese families with primary angle closure glaucoma . Ophthalmic Genet. 2008, 29 (4): 171-176.PubMed
222.
Teikari J, Koskenvuo M, Kaprio J, O’Donnell J: Study of gene-environment effects on development of hyperopia: a study of 191 adult twin pairs from the Finnish Twin Cohort Study . Acta Genet Med Gemellol. 1990, 39: 133-136.PubMed
223.
Lee M, Cho S, Kim H, Song Y, Lee K, Kim J, Kim D, Chung T, Kim Y, Seo J, Ham D, Sung J: Epidemiologic characteristics of intraocular pressure in the Korean and Mongolian populations: the Healthy Twin and the GENDISCAN study . Ophthalmology. 2012, 119 (3): 450-457.PubMed
224.
Forsman E, Cantor R, Lu A, Eriksson A, Fellman J, Jrvel I, Forsius H: Exfoliation syndrome: prevalence and inheritance in a subisolate of the Finnish population . Acta Ophthalmol Scand. 2007, 85 (5): 500-507.PubMed
225.
Carbonaro F, Andrew T, Mackey D, Young T, Spector T, Hammond C: Repeated measures of intraocular pressure result in higher heritability and greater power in genetic linkage studies . Invest Ophthalmol Vis Sci. 2009, 50 (11): 5115-5119.PubMedPubMedCentral
226.
Heitmann M, Hamann H, Brahm R, Grussendorf H, Rosenhagen C, Distl O: Analysis of prevalence of presumed inherited eye diseases in Entlebucher Mountain Dogs . Vet Ophthalmol. 2005, 8 (3): 145-151.PubMed
227.
Hammond C, Snieder H, Spector T, Gilbert C: Genetic and environmental factors in age-related nuclear cataracts in monozygotic and dizygotic twins . N Engl J Med. 2000, 342 (24): 1786-1790.PubMed
228.
Lyhne N, Sjlie A, Kyvik K, Green A: The importance of genes and environment for ocular refraction and its determiners: a population based study among 20-45 year old twins . Br J Ophthalmol. 2001, 85 (12): 1470-1476.PubMedPubMedCentral
229.
Tsai M, Lin L, Lee V, Chen C, Shih Y: Estimation of heritability in myopic twin studies . Jpn J Ophthalmol. 2009, 53 (6): 615-622.PubMed
230.
Gilmartin B: Myopia: precedents for research in the twenty-first century . Clin Experiment Ophthalmol. 2004, 32 (3): 305-324.PubMed
231.
Stefan MP: Genetic linkage analysis . Arch Neurol. 1999, 56 (6): 667-672.
232.
Consortium WTCC: Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls . Nature. 2007, 447 (7145): 661-678.
233.
McKusick-Nathans Institute of Genetic Medicine and Johns Hopkins University (Baltimore, MD): Online Mendelian Inheritance in Man, OMIM . [http://​omim.​org/​],
234.
Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, Smith HO, Yandell M, Evans CA, Holt RA, Gocayne JD, Amanatides P, Ballew RM, Huson DH, Wortman JR, Zhang Q, Kodira CD, Zheng XH, Chen L, Skupski M, Subramanian G, Thomas PD, Zhang J, Gabor Miklos GL, Nelson C, Broder S, Clark AG, Nadeau J, McKusick VA, Zinder N, et al: The sequence of the human genome . Science. 2001, 291 (5507): 1304-1351.PubMed
235.
236.
Klein R, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C: Complement factor H polymorphism in age-related macular degeneration . Science. 2005, 308 (5720): 385-389.PubMedPubMedCentral
237.
Cooper JD, Smyth DJ, Smiles AM, Plagnol V, Walker NM, Allen JE, Downes K, Barrett JC, Healy BC, Mychaleckyj JC, Warram JH, Todd JA: Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci . Nat Genet. 2008, 40 (12): 1399-1401.PubMedPubMedCentral
238.
Fung HC, Scholz S, Matarin M, Simon-Sanchez J, Hernandez D, Britton A, Gibbs JR, Langefeld C, Stiegert ML, Schymick J, Okun MS, Mandel RJ, Fernandez HH, Foote KD, Rodríguez RL, Peckham E, De Vrieze FW, Gwinn-Hardy K, Hardy JA, Singleton A: Genome-wide genotyping in Parkinson’s disease and neurologically normal controls: first stage analysis and public release of data . Lancet Neurol. 2006, 5 (11): 911-916.PubMed
239.
Larson M, Atwood L, Benjamin E, Cupples LA, D’Agostino R, Fox C, Govindaraju D, Guo CY, Heard-Costa N, Hwang SJ, Murabito JM, Newton-Cheh C, O’Donnell CJ, Seshadri S, Vasan RS, Wang TJ, Wolf PA, Levy D: Framingham Heart Study 100K project: genome-wide associations for cardiovascular disease outcomes . BMC Med Genet. 2007, 8 (Suppl 1): S5-PubMedPubMedCentral
240.
Scuteri A, Sanna S, Chen WM, Uda M, Albai G, Strait J, Najjar S, Nagaraja R, Orru M, Usala G, Dei M, Lai S, Maschio A, Busonero F, Mulas A, Ehret GB, Fink AA, Weder AB, Cooper RS, Galan P, Chakravarti A, Schlessinger D, Cao A, Lakatta E, Abecasis GR: Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits . PLoS Genet. 2007, 3 (7): e115-PubMedPubMedCentral
241.
Kooperberg C, LeBlanc M, Obenchain V: Risk prediction using genome-wide association studies . Genet Epidemiol. 2010, 34 (7): 643-652.PubMedPubMedCentral
242.
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M, Bender D: PLINK: a toolset for whole-genome association and population-based linkage analysis . Am J Hum Genet. 2007, 81 (3): 559-575.PubMedPubMedCentral
243.
Marchini J, Howie B: Genotype imputation for genome-wide association studies . Nat Rev Genet. 2010, 11 (7): 499-511.PubMed
244.
Wan X, Yang C, Yang Q, Yang H, Xue H, Fan X: BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies . Am J Hum Genet. 2010, 87 (3): 325-340.PubMedPubMedCentral
245.
Zhang X, Huang S, Zou F, Wang W: TEAM: efficient two-locus epistasis tests in human genome-wide association study . Bioinformatics. 2010, 26 (12): i217—227-
246.
Wu J, Devlin B, Ringquist S: Screen and clean: A tool for identifying interactions in genome-wide association studies . Genet Epidemiol. 2010, 34 (3): 275-285.PubMedPubMedCentral
247.
Tibshirani R: Regression shrinkage and selection via the lasso . J R Statist Soc B. 1996, 58: 267-288.
248.
Wu T, Chen Y, Hastie T, Sobel E, Lange K: Genome-wide association analysis by lasso penalized logistic regression . Bioinformatics. 2009, 25 (6): 714-21.PubMedPubMedCentral
249.
Wu A, Aporntewan C, Ballard D, Lee J, Lee J, Zhao H: Two-stage joint selection method to identify candidate markers from genome-wide association studies . BMC Proc. 2009, 3 (7): s29-PubMedPubMedCentral
250.
Hoggart C, Whittaker J, De Iorio M, Balding D: Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies . PLoS Genet. 2008, 4 (7): e1000130-PubMedPubMedCentral
251.
D’Angelo G, Rao D, Gu C: Combining least absolute shrinkage and selection operator (LASSO) and principal-components analysis for detection of gene-gene interactions in genome-wide association studies . BMC Proc. 2009, 3 (7): S62-PubMedPubMedCentral
252.
Li C, Li M, Lange E, Watanabe R: Prioritized subset analysis: improving power in genome-wide association studies . Hum Hered. 2008, 65 (3): 129-141.PubMed
253.
Shortliffe EH: Mycin: A knowledge-based computer program applied to infectious diseases . Proceedings of Annu Symp Comput Appl Med Care, Washington, USA. 1977, Bethesda, Maryland: American Medical Informatics Association, 66-9.
254.
Miller R, Pople HJ, Myers J: Internist-I, an experimental computer-based diagnostic consultant for general internal medicine . N Engl J Med. 1982, 307 (8): 468-476.PubMed
255.
Drent M, van Nierop MA, Gerritsen FA, FWouters E, Mulder PG: A computer program using BALF-analysis results as a diagnostic tool in interstitial lung diseases . Am J Respi Crit Care Med. 1996, 153 (2): 736-741.
256.
Raza S, Sharma Y, Chaudry Q, Young AN, Wang MD: Automated classification of renal cell carcinoma subtypes using scale invariant feature transform . Conf Proceedings IEEE Eng Med Biol Soc, Minnesota, USA. 2009, IEEE, 6687-690.
257.
Miller GA: The magical number seven plus or minus two: some limits on our capacity for processing information . Psychol Rev. 1956, 63 (2): 81-87.PubMed
258.
Guyatt G, Rennie D, Meade MO, Cook DJ: Users guides to the medical literature: evidence-based medicine . JAMA: J Am Med Assoc. 2000, 284 (10): 1290-296.
259.
Haug P, Clayton PD, Shelton P, Rich T, Tocino I, Frederick PR, Crapo RO, Morrison WJ, Warner HR: Revision of diagnostic logic using a clinical database . Med Decis Making. 1989, 9 (2): 84-90.PubMed
260.
BWagholikar K, Sundararajan V, Deshpande AW: Modeling paradigms for medical diagnostic decision support: a survey and future directions . J Med Syst. 2012, 36 (5): 3029-3049.
261.
Aronsky D, Chan J, Haug PJ: Evaluation of a computerized diagnostic decision support system for patients with pneumonia: study design considerations . J Am Med Inform Assoc. 2001, 8 (5): 473-85.PubMedPubMedCentral
262.
Mustacchi G, Sormani M, Bruzzi P, Gennari A, Zanconati F, Bonifacio D, Monzoni A, Morandi L: Identification and validation of a new set of five genes for prediction of risk in early breast cancer . Int J Mol Sci. 2013, 14 (5): 9686-9702.PubMedPubMedCentral
263.
Zhang Z, Yin FS, Liu J, Wong WK, Tan NM, Lee BH, Cheng J, Wong TY: ORIGA-light: an online retinal fundus image database for glaucoma analysis and research . Conf Proceedings of IEEE Eng Med Biol Soc, Istanbul, Turkey. 2010, IEEE,
264.
Lauterwald F, Neumann CP, Lenz R, Junemann AG, Mardin CY, Meyer-Wegener K, Horn FK: The Erlangen Glaucoma registry: a scientific database for longitudinal analysis of glaucoma . Technical Report CS-2011-02. 2011, University of Erlangen, Dept. of Computer Science,
265.
Budai A, Odstricilik J, Kollar R, Jan J, Kubena T, Michelson G: A public database for the evaluation of fundus image segmentation algorithms . Proceedings of The Association of Research in Vision and Ophthalmology (ARVO) Annual Meeting, Vancouver, Canada. 2011, Rockville, Maryland: ARVO, 1345-1345.
266.
Hofman A, van Duijn CM, Franco OH, Ikram MA, Janssen HL, Klaver CC, Kuipers EJ, Nijsten TE, Stricker BH, Tiemeier H, Uitterlinden AG, Vernooij MW, Witteman JC: The Rotterdam study: 2012 objectives and design update . Eur J Epidemiol. 2011, 26 (8): 657-686.PubMedPubMedCentral
267.
Kauppi T, Kalesnykiene V, Kamarainen JK, Lensu L, Sorri I, Uusitalo H, Kaviainen H, Pietila J: DIARETDB0: Evaluation database and methodology for diabetic retinopathy algorithms . Machine Vision and Pattern Recognition Research Group, Lappeenranta University of Technology, Finland. 2006,
268.
Kauppi T, Kalesnykiene V, Kamarainen JK, Lensu L, Sorri I, Raninen A, Voutilainen R, Uusitalo H, Kalviainen H, Pietila J: The DIARETDB1 diabetic retinopathy database and evaluation protocol . Proceedings of the British Machine Vision Conference, Warwick, UK. 2007, Durham: BMVA, 15-1.
269.
Niemeijer M, van Ginneken B, Cree MJ, Mizutani A, Quellec G, Sanchez CI, Zhang B, Hornero R, Lamard M, Muramatsu C, Wu X, Cazuguel G, You J, Mayo A, Li Q, Hatanaka Y, Cochener B, Roux C, Karray F, Garcia M, Fujita H, Abramoff MD: Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs . IEEE Trans Med Imaging. 2010, 29 (1): 185-195.PubMed
270.
271.
Gangnon R, Lee L, Hubbard L, Klein B, Klein R, Ferris F, Bressler S, Milton RC, Davis M: The Age-related eye disease study severity scale for age-related macular degeneration: AREDS report No. 17 . Arch Ophthalmol. 2005, 123 (11): 1484-PubMed
272.
Wong DW, Liu J, Cheng X, Zhang J, Yin F, Bhargava M, Cheung GC, Wong TY: THALIA-An automatic hierarchical analysis system to detect drusen lesion images for amd assessment . Proceedings of IEEE Int Symposium Biomedical Imaging, Francisco, USA. 2013, IEEE, 884-887.
273.
CAPT study group: The complications of age-related macular degeneration prevention trial (CAPT): rationale, design and methodology . Clin Trials. 2004, 1: 91-107.
274.
Kanthan GL, Mitchell P, Rochtchina E, Cumming RG, Wang JJ: Myopia and the long-term incidence of cataract and cataract surgery: the blue mountains eye study . Clin Exp Ophthalmol. 2013, 42 (4): 347-353.
275.
Zhao L, Wang Y, Chen CX, Xu L, Jonas JB: Retinal nerve fibre layer thickness measured by Spectralis spectral-domain optical coherence tomography: The Beijing Eye Study . Acta ophthalmologica. 2013,
276.
Asakuma T, Yasuda M, Ninomiya T, Noda Y, Arakawa S, Hashimoto S, Ohno-Matsui K, Kiyohara Y, Ishibashi T: Prevalence and risk factors for myopic retinopathy in a Japanese population: the Hisayama Study . Ophthalmology. 2012, 119 (9): 1760-1765.PubMed
277.
Chen SJ, Cheng CY, Li AF, Peng KL, Chou P, Chiou SH, Hsu WM: Prevalence and associated risk factors of myopic maculopathy in elderly Chinese: the Shihpai eye study . Invest Ophthalmol Vis Sci. 2012, 53 (8): 4868-4873.PubMed
278.
Noronha K, Acharya UR, Nayak KP, Kamath S, Bhandary SV: Decision support system for diabetic retinopathy using discrete wavelet transform . Proc Inst Mech Eng Part H: J Eng Med. 2013, 227 (3): 251-261.
279.
Larsen N, Godt J, Grunkin M, Lund-Andersen H, Larsen M: Automated detection of diabetic retinopathy in a fundus photographic screening population . Invest Ophthalmol Vis Sci. 2003, 44 (2): 767-771.PubMed
280.
Hansen AB, Hartvig NV, Jensen MS, Borch-Johnsen K, Lund-Andersen H, Larsen M: Diabetic retinopathy screening using digital non-mydriatic fundus photography and automated image analysis . Acta Ophthalmologica Scandinavica. 2004, 82 (6): 666-672.PubMed
281.
Sharma A, Sobti A, Wadhwani M, Panda A: Evaluation of retinal nerve fiber layer using scanning laser polarimetry . J Curr Glaucoma Prac. 2010, 4 (3): 240-251.
282.
Potsaid B, Baumann B, Huang D, Barry S, Cable AE, Schuman JS, Duker JS, Fujimoto JG: Ultrahigh speed 1050 nm swept source/Fourier domain OCT retinal and anterior segment imaging at 100,000 to 400,000 axial scans per second . Optics Express. 2010, 18 (19): 20029-48.PubMedPubMedCentral
283.
Asbell P, Dualan I, Mindel J, Brocks D, Ahmad M, Epstein S: Age-related cataract . The Lancet. 2005, 365 (9459): 599-609.
284.
Xu Y, Gao X, Wong DW, Liu J, Xu D, Cheng CY, Cheung CYL, Wong TY: Automatic Grading of Nuclear Cataracts from Slit-lamp Lens Images Using Group Sparsity Regression . Proceedings Int Conf MICCAI, Nagoya, Japan, MICCAI. 2013, Heidelberg: Springer Berlin, 468-475.
285.
Li H, Lim JH, Liu J, Wong DWK, Foo Y, Sun Y, Wong TY: Automatic detection of posterior subcapsular cataract opacity for cataract screening . Conf Proceedings of IEEE Eng Med Biol Soc, Istanbul, Turkey. 2010, IEEE, 5359-5362.
286.
McCally RL, Hochheimer BF, Chamon W, Azar DT: Simple device for objective measurements of haze following excimer laser ablation of cornea . OE/LASE’93: Optics, Electro-Optics, & Laser Applications in Science & Engineering, Los Angeles, USA. 1993, Bellingham: International Society for Optics and Photonics, 20-25.
287.
McCally RL, Connolly PJ, Jain S, Azar DT: Objective measurements of haze following phototherapeutic excimer laser ablation of cornea . OE/LASE’94: Optics, Electro-Optics, & Laser Applications in Science & Engineering, Los Angeles, USA. 1994, Bellingham: International Society for Optics and Photonics, 161-165.
288.
Taboada J, Gaines D, Perez MA, Waller SG, Ivan DJ, Baldwin JB, LoRusso F, Tutt RC, Perez J, Tredici T, Johnson DA: Post-PRK corneal scatter measurements with a scanning confocal slit photon counter . BiOS 2000 The International Symposium on Biomedical Optics, San Jose, USA. 2000, Bellingham: International Society for Optics and Photonics, 50-59.
289.
Taboada J, Gaines D, Perez MA, Waller SG, Ivan DJ, Baldwin JB, LoRusso F, Tutt RC, Thompson B, Perez J, Tredici T, Johnson DA: Scanning confocal slit photon counter measurements of post-PRK haze in two-year study . BiOS 2001 The International Symposium on Biomedical Optics. 2001, Bellingham: International Society for Optics and Photonics, 7-17.
290.
Acharya U, Kannathal N, Ng E, Min L, Suri J: Computer-based classification of eye diseases . Conf Proceedings of IEEE Eng Med Biol Soc, New York, USA. 2006, 6121-6124.
291.
Acharya UR, Wong L, Ng E, Suri J: Automatic identification of anterior segment eye abnormality . IRBM. 2007, 28: 35-41.
Metadata
Title
A survey on computer aided diagnosis for ocular diseases
Authors
Zhuo Zhang
Ruchir Srivastava
Huiying Liu
Xiangyu Chen
Lixin Duan
Damon Wing Kee Wong
Chee Keong Kwoh
Tien Yin Wong
Jiang Liu
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2014
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/1472-6947-14-80

Other articles of this Issue 1/2014

BMC Medical Informatics and Decision Making 1/2014 Go to the issue

Research article

A simulation model of colorectal cancer surveillance and recurrence

Research article

Congruence between patients’ preferred and perceived participation in medical decision-making: a review of the literature

Research article

Development of a culturally appropriate computer-delivered tailored internet-based health literacy intervention for spanish-dominant hispanics living with HIV

Research article

Accuracy of automatic syndromic classification of coded emergency department diagnoses in identifying mental health-related presentations for public health surveillance

Correspondence

Technical challenges of providing record linkage services for research

Research article

Designing privacy-friendly digital whiteboards for mediation of clinical progress