« Previous
Next »
Computerized Medical Imaging and Graphics
Volume 33, Issue 8
, Pages 608-622
, December 2009
Algorithms for digital image processing in diabetic retinopathy
References
- . Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004;27:1047–1053
- The value of digital imaging in diabetic retinopathy. Health Technol Assess. 2003;7:1–119
- . Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels. IEEE Trans Med Imaging. 2003;22:951–958
- . An approach to the space variant restoration and enhancement of images. In: Proceedings of the symposium on current mathematical problems in imaging science. Naval Postgraduate School, Monterey. 1976;p. 329–340
- . Digital Image Processing. Prentice Hall; 2002;
- . Luminosity and contrast normalization in retinal images. Med Imaging Anal. 2005;9:179–190
- . The preprocessing of retinal images for the detection of fluorescein leakage. Phys Med Biol. 1999;44:293–308
- . Detection of optic disc in retinal images by means of a geometrical model of vessel structure. IEEE Trans Med Imaging. 2004;23:1189–1195
- . An image-processing strategy for the segmentation and quantification of microaneurysms in fluorescein angiograms of the ocular fundus. Comp Biomed Res. 1996;29:284–302
- . Measurement of capillary dropout in retinal angiograms by computerised image analysis. Pattern Recogn Lett. 1992;13:143–151
- . Image analysis of fundus photographs: the detection and measurement of exudates associated with diabetic retinopathy. Ophthalmology. 1989;96:80–86
- Øien G, Osnes P. Diabetic retinopathy: automatic detection of early symptoms from retinal images. In proceedings of NORSIG-95 Norwegian signal processing symposium 1995. Available at http://www.ux.his.no/sigproc/www/norsig/norsig95.html.
- . A computational approach to diagnosis of diabetic retinopathy. In: Proceedings of the 6th conference on systemics, cybernetics and informatics (SCI). 2002;p. 521–526
- . An effective approach to detect lesions in color retinal images. In: IEEE conference on computer vision and pattern recognition. 2000;p. 1–6
- . Illumination normalization of retinal images using sampling and interpolation. Proc SPIE Med Imaging 2001: Image Process. 2001;4322:500–507
- . The discrimination of similarly colored objects in images of the ocular fundus. Invest Ophthalmol Vis Sci. 1990;31:617–623
- . Computer-assisted, interactive fundus image processing for macular drusen quantitation. Ophthalmology. 1999;106:1119–1125
- . Blood vessels segmentation in nonmydriatic images using wavelets and statistical classifiers. In: XVI Brazilian symposium on computer graphics and image processing. 2003;p. 262–269
- . Detection and segmentation of drusen deposits on human retina: potential in the diagnosis of age-related macular degeneration. Med Imaging Anal. 2003;7:95–108
- . Fundus reflectance-historical and present ideas. Prog Retin Eye Res. 2003;22:171–200
- . Automated localisation of the optic disc, fovea, and retinal blood vessels from digital color fundus images. Br J Ophthalmol. 1999;83:902–910
- Osareh A. Automated identification of diabetic retinal exudates and the optic disc. Ph.D. thesis. University of Bristol; 2004.
- . Color normalisation of retinal images. In: Proceedings medical image understanding and analysis. 2003;p. 49–52
- . Automated identification of diabetic retinal exudates in digital color images. Br J Ophthalmol. 2003;87:1220–1223
- Cree MJ, Gamble E, Cornforth D. Color normalisation to reduce inter-patient and intra-patient variability in microaneurysm detection in color retinal images, WDIC2005 ARPS workshop on digital image computing, Brisbane, Australia, 2005. p. 163–8.
- . Perceived image contrast and observer preference I. the effects of lightness, chroma, and sharpness manipulations on contrast perception. J Imaging Sci Technol. 2003;47:479–493
- . Automated detection of diabetic retinopathy in digital retinal images: a tool for diabetic retinopathy screening. Diabet Med. 2004;21:84–90
- Optic nerve head segmentation. IEEE Trans Med Imaging. 2004;23:256–264
- Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study. Ophthalmology. 1999;106:2269–2280
- . Non-recursive paired tracking for vessel extraction from retinal images. In: Proceedings of the conference vision interface. 2000;p. 61–68
- . Automatic detection of the optic nerve in retinal images. In: IEEE international conference on imaging processing, vol. 1. 1989;p. 1–5
- Automated diagnosis and image understanding with object extraction, object classification, and inferencing in retinal images. In: Proceedings IEEE international conference on image processing, vol. 3. 1996;p. 695–698
- . Recognizing the glaucoma from ocular fundus image by image analysts. In: Proceedings of the 12th international conference of the IEEE engineering in medicine and biology society. 1990;p. 178–179
- . Mapping the human retina. IEEE Trans Med Imaging. 1998;17:606–619
- . Automatic image analysis of fundus photograph. In: Proceedings 19th international conference IEEE engineering in medicine and biology society. 1997;p. 524–525
- . Course tracking and contour extraction of retinal vessels from color fundus photographs: most efficient use of steerable filters for model based image analysis. In: SPIE conference image processing, vol. 3338. 1998;p. 755–761
- Screening for diabetic retinopathy using computer based image analysis and statistical classification. Comput Methods Programs Biomed. 2000;62:165–175
- Automated segmentation of the optic nerve head for diagnosis of glaucoma. Med Image Anal. 2005;9:297–314
- . Automated feature extraction in color retinal images by a model based approach. IEEE Trans Biomed Eng. 2004;51:246–254
- . Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy. In: Proceedings of the 26th annual international conference of the IEEE engineering in medicine and biology society, vol. 1. 2004;p. 1624–1627
- . Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching. IEEE Trans Med Imaging. 2001;20:1193–1200
- . A computer method of understanding ocular fundus images. Pattern Recognit. 1982;15:431–443
- . Fuzzy convergence. In: Proceedings IEEE computer society conference on computer vision and pattern recognition. 1998;p. 716–721
- . Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Trans Med Imaging. 2000;19:203–210
- . Detection of vessel caliber irregularities in color retinal fundus images by means of fine tracking. In: Proceedings of the 2nd European medical and biological engineering conference. 2002;
- . Segmentation of color fundus images of the human retina: detection of the optic disc and the vascular tree using morphological techniques. In: Second international symposium on medical data analysis. 2001;p. 282–287
- . Snakes: active contour models. Int J Comput Vis. 1987;1:321–331
- . Integrating stereo and photometric stereo to monitor the development of glaucoma. Image Vision Comput. 1991;9:39–44
- . Extraction of the optic disk boundary in digital fundus images. In: Proceedings of the first joint BMES/EMBS conference. 1999;p. 1139
- . Identification of the optic disc boundary in retinal images using active contours. In: In the proceedings of the Irish machine vision and image processing conference. 1999;p. 103–115
- . Snakes, shapes, and gradient vector flow. IEEE Trans Image Process. 1998;7:359–369
- . Vessel boundary extraction based on a global and local deformable physical model with variable stiffness. Mag Reson Imaging. 1998;16:943–951
- . Measurement of retinal vessel widths from fundus images based on 2-D Modeling. IEEE Trans Med Imaging. 2004;23:1196–1204
- . Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Trans Med Imaging. 1989;8:263–269
- Retinal image analysis: concepts, applications and potential. Prog Retin Eye Res. 2006;25:99–127
- . Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis. Med Image Anal. 2002;6:407–429
- A computer-aided diagnostic detection system of venous beading in retinal images. Opt Eng. 2000;39:1293–1303
- . Robust segmentation of vessels from retinal angiography. In: Proceedings of international conference on digital signal processing. 1997;p. 1087–1090
- . A multimodal registration algorithm of eye fundus images using vessels detection and Hough transform. IEEE Trans Med Imaging. 1999;18:419–428
- . Automated grading of venous beading. Comput Biomed Res. 1995;28:291–304
- A comparison of computer based classification methods applied to the detection of microaneurysms in ophthalmic fluorescein angiograms. Comput Biol Med. 1998;28:225–238
- . Progress towards automated diabetic ocular screening: a review of image analysis and intelligent systems for diabetic retinopathy. IEEE Med Biol Eng Comput. 2002;40:2–13
- . A model-based approach for automated feature extraction in fundus image. In: Proceedings of the ninth IEEE international conference on computer vision, vol. 1. 2003;p. 394–399
- . Integrated analysis of vascular and nonvascular changes from color retinal fundus image sequences. Biomed Eng IEEE Trans. 2007;54(8):1436–1445
- . Detection of anatomic structures in human retinal imagery. IEEE Trans Med Imag. 2007;26(12):1729–1739
- . A fully automated comparative microaneurysm digital detection system. Eye. 1997;11:622–628
- . Automated measurement of microaneurysm turnover. Invest Ophthalmol Vis Sci. 2003;44:5335–5341
- . Automated detection of microaneurysms in digital red-free photographs: a diabetic retinopathy screening tool. Diab Med. 2000;17:588–594
- . Methodology for retinal photography and assessment of diabetic retinopathy: the EURODIAB IDDM complications study. Diabetologia. 1995;38:437–444
- . Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. Br J Ophthalmol. 1996;80:940–944
- Automated detection of diabetic retinopathy on digital fundus images. Diabet Med. 2002;19:105–112
- Comparison of diagnosis of early retinal lesions of diabetic retinopathy between a computer system and human experts. Arch Ophthalmol. 2001;119:509–515
- . Automated detection of diabetic retinopathy in a fundus photographic screening population. Invest Ophthalmol Vis Sci. 2003;44:767–771
- . Evaluation of a system for automatic detection of diabetic retinopathy from color fundus photographs in a large population of patients with diabetes. Diabetes Care. 2008;31(2):193–198
- Standards for reporting of diagnostic accuracy. toward complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Standards for Reporting of Diagnostic Accuracy. Clin Chem. 2003;49:19–20
- . Optic disc detection from normalized digital fundus images by means of a vessels’ direction matched filter. IEEE Trans Med Imaging. 2008;27(1):11–18
- . Morphology approach for features extraction in retinal images for diabetic retionopathy diagnosis. Comput Commun Eng. 2008;1373–1377
- . Preliminary results on using an extension of gradient method for detection of red lesions on eye fundus photographs. Automation, quality and testing, robotics, IEEE international conference. 2008;3:43–48
- . Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms. IEEE Trans Inf Technol Biomed. 1999;3:125–138
- . A feature-based, robust, hierarchical algorithm for registering pairs of images of the curved human retina. IEEE Trans Pattern Anal Mach Intell. 2002;24:347–364
- . A feature-based technique for joint, linear estimation of high-order image-to-mosaic transformations: mosaicing the curved human retina. IEEE Trans Pattern Anal Mach Intell. 2002;24:412–419
- . An efficient blood vessel detection algorithm for retinal images using local entropy thresholding. In: Proceedings of the international symposium on circuits and systems, vol. 5. 2003;p. 21–24
- . Hybrid retinal image registration. IEEE Trans Inform Technol Biomed. 2006;10:129–142
- Computer algorithms for the automated measurement of retinal arteriolar diameters. Br J Ophthalmol. 2001;85:74–79
- . Retinal blood vessel detection and tracking by matched Gaussian and Kalman filters. In: Proceedings of IEEE EMBS, vol. 20. 1998;p. 3144–3149
- . Ocular fundus coordinate establishment. In: proceedings of the 24th engineering in medicine and biology annual conference and the annual fall meeting of the biomedical engineering society conference, vol. 3. 2002;p. 2141–2142
- Development of retinal blood vessel segmentation methodology using wavelet transforms assessment of diabetic retinopathy. In: Eighth Asia pacific symposium on intelligent and evolutionary systems. 2004;p. 50–60
- . Neural network based retinal image analysis. Congress Image Signal Process. 2008;2:49–53
- . Design and implementation of a unique blood-vessel detection algorithm towards early diagnosis of diabetic retinopathy. In: International conference on information technology: coding and computing, vol. 1. 2005;p. 26–31
- . Automatic detection and diagnosis of diabetic retinopathy. In: IEEE international conference on image processing, vol. 2. 2007;p. 445–448
- . Blood vessel detection via a multi-window parameter transform. In: 19th IEEE international symposium on computer-based medical systems. 2006;p. 424–429
- . Extraction of the contours of optic disc and exudates based on marker-controlled watershed segmentation. In: International conference on computer science and information technology. 2008;p. 719–723
- . Reconstruction of vascular structures in retinal images. In: Proceedings international conference on image processing, vol. 2. 2003;p. 157–160
- . Automatic detection of retinal anatomy to assist diabetic retinopathy screening. Phys Med Biol. 2007;52(2):331–345
- . Automated detection of exudates for diabetic retinopathy screening. Phys Med Biol. 2007;52(24):7385–7396
- . Procedure to detect anatomical structures in optical fundus images. Proc SPIE Med Imaging: Image Process. 2001;4322:1218–1225
- . Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter. IEEE Trans Biomed Eng. 2002;49:168–172
- . Abnormality detection in automated mass screening system of diabetic retinopathy. In: Proceedings of 14th IEEE symposium on computer-based medical systems. 2001;p. 132–137
- . Quantification and characterisation of arteries in retinal images. Comput Methods Programs Biomed. 2000;63:133–146
- . Measurement of vessel diameters on retinal images for cardiovascular studies. In: Proceedings medical image understanding and analysis. 2001;
- . A method of vessel tracking for vessel diameter measurement on retinal images. In: Proceedings international conference on image processing, vol. 2. 2001;p. 881–884
- . Feature extraction and selection for the automatic detection of hard exudates in retinal images. In: 29th annual international conference of the IEEE engineering in medicine and biology society. 2007;p. 4969–4972
- . ADRIS: an automatic diabetic retinal image screening system. In: Cois KJ editors. Medical data mining and knowledge discovery, 60, studies in fuzziness and soft computing. Physica-Verlag; 2001;p. 181–210
- . A new tracking system for the robust extraction of retinal vessel structure. In: Proceedings of IEEE international conference engineering and biology society. 2004;p. 1620–1623
- . Segmentation of candidate dark lesions in fundus images based on local thresholding and pixel density. In: 29th international conference of the IEEE engineering in medicine and biology society. 2007;p. 6735–6738
- . Localization of the optic disk in retinal image using the ‘watersnake’. In: International conference on computer and communication engineering. 2008;p. 947–951
- . Diabetic retinopathy screening using digital non-mydriatic fundus photography and automated image analysis. Acta Ophthalmol Scand. 2004;82:666–672
- A development of computer-aided diagnosis system using fundus images. In: Seventh international conference on virtual systems and multimedia. 2001;p. 429
- . Optimal scheduling of tracing computations for real-time vascular landmark extraction from retinal fundus images. IEEE Trans Inform Technol Biomed. 2001;5:77–91
- . Frame-rate spatial referencing based on invariant indexing and alignment with application to online retinal image registration. IEEE Trans Pattern Anal Mach Intell. 2003;25:379–384
- . The role of domain knowledge in the detection of retinal hard exudates. In: Proceedings IEEE computer society conference on computer vision and pattern recognition, vol. 2. 2001;p. 246–251
- . Blood vessel tracking technique for optic nerve localisation for field 1–3 color fundus images. In: Proceedings of the joint conference of the fourth international conference on information, communications and signal processing, and the fourth pacific rim conference on multimedia, vol. 3. 2003;p. 1437–1441
- . Detection of vascular intersection in retina fundus image using modified cross point number and neural network technique. Int Conf Comput Commun Eng. 2008;241–246
- . Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Trans Pattern Anal Mach Intell. 2003;25:131–137
- . Decision support for automated screening of diabetic retinopathy. In: Conference record of the thirty-eighth asilomar conference on signals, systems and computers, vol. 2. 2004;p. 1630–2344
- . A decision support framework for automated screening of diabetic retinopathy. Int J Biomed Imaging. 2006;1–8
- . Boucher automatic visual quality assessment in optical fundus images. In: Proceedings of vision interface. 2001;p. 259–264
- . Screening of diabetic retinopathy—automatic segmentation of optic disc in colour fundus images. In: The second international conference on distributed frameworks for multimedia applications. 2006;p. 1–7
- . Automated detection of venous beading in retinal images. Proc SPIE Med Imaging Process. 2001;4322:1365–1372
- . Fundus image features extraction. In: Proceeding of 22nd IEEE international conference engineering in medicine and biology society. 2000;p. 3071–3073
- . Automatic location of the optic disk in retinal images. In: Proceedings of IEEE international conference imaging processing. 2001;p. 837–840
- . Automatic grading of retinal vessel caliber. IEEE Trans Biomed Eng. 2005;52:1352–1355
- . Abnormality detection in automated mass screening system of diabetic retinopathy. In: Proceedings 14th IEEE symposium on computer-based medical systems. 2001;p. 132–137
- . Robust model-based vasculature detection in noisy biomedical images. IEEE Trans Inform Technol Biomed. 2004;8:360–376
- Retinal vascular tree morphology: a semi-automatic quantification. IEEE Trans Biomed Eng. 2002;49:912–917
- 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
- . Automated identification of diabetic retinopathy stages using digital fundus images. J Med Syst. 2008;32(2):107–115
- . Automatic detection of red lesions in digital color fundus photographs. IEEE Trans Med Imaging. 2005;24:584–592
- . 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
- . Segmentation of the optic disc, macula and vascular arch in fundus photographs. IEEE Trans Med Imaging. 2007;26(1):116–127
- . Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Fitzpatrick JM, Sonka M editor. SPIE medical imaging. vol. 5370:2004;p. 648–656
- . Enhancement of retinal fundus image to highlight the features for detection of abnormal eyes. In: TENCON 2006. IEEE region 10 conference. 2006;p. 1–4
- . Comparison of color spaces for optic disc localisation in retinal images. In: Proceedings of 16th international conference on pattern recognition, vol. 1. 2002;p. 743–746
- . Automated microaneurysm segmentation and detection using generalized Eigenvectors. In: Seventh IEEE workshop on application of computer vision, vol. 1. 2005;p. 322–327
- Quantitative measurement of changes in retinal vessel diameter in ocular fundus images. Pattern Recogn Lett. 2000;21:1215–1223
- . Image segmentation of retinal vessels by fuzzy models. In: Proceedings of 2005 international symposium on intelligent signal processing and communication systems. 2005;p. 541–544
- . Detection of lesions in retina photographs based on the wavelet transform. In: 28th annual international conference of the IEEE engineering in medicine and biology society. 2006;p. 2618–2621
- . Optimal wavelet transform for the detection of microaneurysms in retina photographs. IEEE Trans Med Imaging. 2008;27(9):1230–1241
- . The effects of spatial resolution on an automated diabetic retinopathy screening system's performance in detecting microaneurysms for diabetic retinopathy. In: Proceedings of the 17th IEEE symposium on computer-based medical systems, CBMS. 2004;p. 128–133
- . A novel integrated approach using dynamic thresholding and edge detection (IDTED) for automatic detection of exudates in digital fundus retinal images. In: International conference on computing: theory and applications. 2007;p. 705–710
- . Automatic image processing algorithm to detect hard exudates based on mixture models. In: 28th annual international conference of the IEEE engineering in medicine and biology society. 2006;p. 4453–4456
- . Performance enhancement of optic disc boundary detection using active contours via improved homogenization of optic disc region. In: International conference on information and automation. 2006;p. 264–269
- . Detection of diabetic retinopathy in fundus images using vector quantization technique. In: Annual India conference. 2006;p. 1–4
- . Automated localisation of retinal optic disk using Hough transform. In: 5th IEEE international symposium on biomedical imaging: from nano to macro. 2008;p. 1577–1580
- . Automated screening system for diabetic retinopathy. In: Proceedings of the 3rd international symposium on image and signal processing and analysis, ISPA, vol. 2. 2003;p. 915–920
- . Development of computer-aided diagnosis system for early diabetic retinopathy based on micro aneurysms detection from retinal images. In: Proceedings of 7th international workshop on enterprise networking and computing in healthcare industry, 2005. HEALTHCOM. 2005;p. 364–367
- . Ridge based vessel segmentation in color images of the retina. IEEE Trans Med Imaging. 2004;23:501–509
- . Retinal blood vessel detection using frequency analysis and local-mean-interpolation filters. In: Proceedings of SPIE Vol Med Imaging: Image Processing, vol. 4322. 2001;p. 1373–1384
- . Utility of color information for segmentation of digital retinal images: neural network-based approach. SPIE Med Imaging: Image Process. 1998;3338:1470–1481
- . Model-based method for improving the accuracy and repeatability of estimating vascular bifurcations and crossovers from retinal fundus images. IEEE Trans Inform Technol Biomed. 2004;8:122–130
- . Automated detection and classification of vascular abnormalities in diabetic retinopathy. In: Conference record of the thirty-eighth asilomar conference on signals, systems and computers, vol. 2. 2004;p. 1625–1629
- . Automatic detection of microaneurysms in color fundus images of the human retina by means of the bounding box closing. In: Third international symposium on medical data analysis. 2002;p. 210–220
- . A contribution of image processing to the diagnosis of diabetic retinopathy—detection of exudates in color fundus images of the human retina. IEEE Trans Med Imaging. 2002;21:1236–1243
- . Automatic detection of microaneurysms in color fundus images. Med Image Anal. 2007;11(6):555–566
- . A SVM approach for detection of hemorrhages in background diabetic retinopathy. In: IEEE international joint conference on neural networks, vol. 4. 2005;p. 2435–2440
- . Top-down and bottom-up strategies in lesion detection of background diabetic retinopathy. In: IEEE computer society conference on computer vision and pattern recognition, vol. 2. 2005;p. 422–428
- . Algorithm for detecting micro-aneurysms in low-resolution color retinal images. In Proc Vision Interface. 2001;265–271
- . Detection and classification of bright lesions in color fundus images. In: International conference on image processing, vol. 1. 2004;p. 139–142
PII: S0895-6111(09)00081-0
doi: 10.1016/j.compmedimag.2009.06.003
© 2009 Elsevier Ltd. All rights reserved.
« Previous
Next »
Computerized Medical Imaging and Graphics
Volume 33, Issue 8
, Pages 608-622
, December 2009
