122 B.7 Orientation information from Gabor filters, Thresholding on the, p.123 ,
125 B.10 Vessels segmentation results comparison 126 B.11 Vessels segmentation results comparison, p.127 ,
133 C.6 Vessel projection to the horizontal axis, p.133 ,
Detection and characterisation of the optic disk in glaucoma and diabetic retinopathy, Proceedings of Medical Image Understanding and Analysis, p.129, 2004. ,
Optic Disc Detection From Normalized Digital Fundus Images by Means of a Vessels' Direction Matched Filter, IEEE Transactions on Medical Imaging, vol.27, issue.1, pp.11-18, 2008. ,
DOI : 10.1109/TMI.2007.900326
Micro-aneurysm detection using vessels removal and circular Hough transform, Proceedings of the Nineteenth National Radio Science Conference, pp.421-426, 2002. ,
DOI : 10.1109/NRSC.2002.1022650
Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes, Diabetes Care, vol.31, issue.2, pp.193-198, 2008. ,
DOI : 10.2337/dc07-1312
Automatic Detection of Diabetic Retinopathy and Age-Related Macular Degeneration in Digital Fundus Images, Investigative Opthalmology & Visual Science, vol.52, issue.8, pp.5862-5871, 2011. ,
DOI : 10.1167/iovs.10-7075
An Active Contour Model for Segmenting and Measuring Retinal Vessels, IEEE Transactions on Medical Imaging, vol.28, issue.9, pp.1488-1497, 2009. ,
DOI : 10.1109/TMI.2009.2017941
An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading, IEEE Transactions on Biomedical Engineering, vol.59, issue.6, pp.1720-1726, 2012. ,
DOI : 10.1109/TBME.2012.2193126
Improving microaneurysm detection in color fundus images by using context-aware approaches. Computerized Medical Imaging and Graphics, p.63, 2013. ,
Fundus digital image processing: automated segmentation of the main retinal anatomical structures, p.19, 2011. ,
A Study on Hemorrhage Detection Using Hybrid Method in Fundus Images, Journal of Digital Imaging, vol.10, issue.2, pp.394-404, 2011. ,
DOI : 10.1007/s10278-010-9274-9
Numerical residues Mathematical Morphology: 40 Years On, pp.23-32, 2005. ,
Robust Detection of Microaneurysms for Sight Threatening Retinopathy Screening, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing, pp.520-527, 2008. ,
DOI : 10.1109/ICVGIP.2008.25
Random forests, Machine Learning, vol.45, issue.1, pp.5-32, 2001. ,
DOI : 10.1023/A:1010933404324
<title>A Free Response Approach To The Measurement And Characterization Of Radiographic Observer Performance</title>, Application of Optical Instrumentation in Medicine VI, pp.124-135, 1977. ,
DOI : 10.1117/12.955926
Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms, IEEE Transactions on Information Technology in Biomedicine, vol.3, issue.2, pp.125-138, 1999. ,
DOI : 10.1109/4233.767088
Detection of blood vessels in retinal images using two-dimensional matched filters, IEEE Transactions on Medical Imaging, vol.8, issue.3, pp.263-269, 1989. ,
DOI : 10.1109/42.34715
Fundus Foveal Localization Based on Vessel Model, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp.4440-4444, 2006. ,
DOI : 10.1109/IEMBS.2006.260741
Retinal blood vessel detection and tracking by matched Gaussian and Kalman filters, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286), pp.3144-3149, 1998. ,
DOI : 10.1109/IEMBS.1998.746160
A fully automated comparative microaneurysm digital detection system, Eye, vol.1652, issue.5, pp.622-628, 1997. ,
DOI : 10.1111/j.1365-2362.1970.tb00613.x
National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2??7 million participants, The Lancet, vol.378, issue.9785, pp.37831-37871, 2011. ,
DOI : 10.1016/S0140-6736(11)60679-X
Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters, Journal of the Optical Society of America A, vol.2, issue.7, pp.1160-1169, 1985. ,
DOI : 10.1364/JOSAA.2.001160
Epidemiology of diabetic retinopathy: Expected vs reported prevalence of cases in the French population, Diabetes & Metabolism, vol.35, issue.6, pp.431-438, 2009. ,
DOI : 10.1016/j.diabet.2009.06.002
URL : https://hal.archives-ouvertes.fr/inserm-00394359
Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy, Diabetes & Metabolism, vol.36, issue.3, pp.213-220, 2010. ,
DOI : 10.1016/j.diabet.2010.01.002
URL : https://hal.archives-ouvertes.fr/hal-00836043
OPHDIAT??: Quality-assurance programme plan and performance of the network, Diabetes & Metabolism, vol.34, issue.3, pp.235-242, 2008. ,
DOI : 10.1016/j.diabet.2008.01.004
Enhancing retinal image by the Contourlet transform, Pattern Recognition Letters, vol.28, issue.4, pp.516-522, 2007. ,
DOI : 10.1016/j.patrec.2006.09.007
Statistical analysis of circular data, p.88, 1995. ,
DOI : 10.1017/CBO9780511564345
Automated detection of exudates for diabetic retinopathy screening, Physics in Medicine and Biology, vol.52, issue.24, pp.7385-7422, 2007. ,
DOI : 10.1088/0031-9155/52/24/012
Automated detection of blot haemorrhages as a sign of referable diabetic retinopathy, Proc. Medical Image Understanding and Analysis, p.92, 2008. ,
Automated microaneurysm detection using local contrast normalization and local vessel detection, IEEE Transactions on Medical Imaging, vol.25, issue.9, pp.1223-1232, 2006. ,
DOI : 10.1109/TMI.2006.879953
Automated Assessment of Diabetic Retinal Image Quality Based on Clarity and Field Definition, Investigative Opthalmology & Visual Science, vol.47, issue.3, pp.1120-1125, 2006. ,
DOI : 10.1167/iovs.05-1155
Detection of Optic Disc in Retinal Images by Means of a Geometrical Model of Vessel Structure, IEEE Transactions on Medical Imaging, vol.23, issue.10, pp.1189-1195, 2004. ,
DOI : 10.1109/TMI.2004.829331
Luminosity and contrast normalization in retinal images, Medical Image Analysis, vol.9, issue.3, pp.179-190, 2005. ,
DOI : 10.1016/j.media.2004.07.001
A comparison of computer based classification methods applied to the detection of microaneurysms in ophthalmic fluorescein angiograms, Computers in Biology and Medicine, vol.28, issue.3, pp.225-238, 1998. ,
DOI : 10.1016/S0010-4825(98)00011-0
Theory of communication. part 1: The analysis of information. Electrical Engineers- Part III: Radio and Communication Engineering, Journal of the Institution, vol.93, issue.26, pp.429-441, 1946. ,
Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter, IEEE Transactions on Biomedical Engineering, vol.49, issue.2, pp.168-172, 2002. ,
DOI : 10.1109/10.979356
Assessment of four neural network based classifiers to automatically detect red lesions in retinal images, Medical Engineering & Physics, vol.32, issue.10, pp.1085-1093, 2010. ,
DOI : 10.1016/j.medengphy.2010.07.014
Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool., British Journal of Ophthalmology, vol.80, issue.11, pp.940-944, 1996. ,
DOI : 10.1136/bjo.80.11.940
Microaneurysms detection with the radon cliff operator in retinal fundus images, Medical Imaging 2010: Image Processing, pp.76230-76230, 2010. ,
DOI : 10.1117/12.844442
Automatic retina exudates segmentation without a manually labelled training set, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1396-1400, 2011. ,
DOI : 10.1109/ISBI.2011.5872661
URL : https://hal.archives-ouvertes.fr/hal-00585177
Exudate-based diabetic macular edema detection in fundus images using publicly available datasets, Medical Image Analysis, vol.16, issue.1, pp.216-226 ,
DOI : 10.1016/j.media.2011.07.004
URL : https://hal.archives-ouvertes.fr/hal-00639756
Digital image processing using MATLAB, p.18, 2009. ,
Localization of the optic disk in retinal image using the watersnake, Computer and Communication Engineering ICCCE 2008. International Conference on, pp.947-951, 2008. ,
Automatic exudate detection with improved naïve-bayes classifier, Computer-Based Medical Systems (CBMS), 2012 25th International Symposium on, pp.1-4, 2012. ,
Improvement of automatic hemorrhage detection methods using brightness correction on fundus images, Medical Imaging 2008: Computer-Aided Diagnosis, pp.69153-69154, 2008. ,
DOI : 10.1117/12.771051
Theoretical aspects of gray-level morphology. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.13, issue.6, pp.568-582, 1991. ,
Automated detection of microaneurysms in digital red-free photographs: a diabetic retinopathy screening tool, Diabetic Medicine, vol.41, issue.8, pp.588-594, 2000. ,
DOI : 10.1006/cbmr.1996.0021
Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels, IEEE Transactions on Medical Imaging, vol.22, issue.8, pp.951-958, 2003. ,
DOI : 10.1109/TMI.2003.815900
Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response, IEEE Transactions on Medical Imaging, vol.19, issue.3, pp.203-210, 2000. ,
DOI : 10.1109/42.845178
Connected Filtering and Segmentation Using Component Trees, Computer Vision and Image Understanding, vol.75, issue.3, pp.215-228, 1999. ,
DOI : 10.1006/cviu.1999.0777
Colour Retinal Image Enhancement Based on Domain Knowledge, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing, pp.591-598, 2008. ,
DOI : 10.1109/ICVGIP.2008.70
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.505.3520
Automated Detection of Malarial Retinopathy-Associated Retinal Hemorrhages, Investigative Opthalmology & Visual Science, vol.53, issue.10, pp.536582-6588, 2012. ,
DOI : 10.1167/iovs.12-10191
Detection of red lesions in digital fundus images, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.558-561, 2009. ,
DOI : 10.1109/ISBI.2009.5193108
Automatic Detection of Microaneurysms and Hemorrhages in Digital Fundus Images, Journal of Digital Imaging, vol.22, issue.8, pp.430-437, 2010. ,
DOI : 10.1007/s10278-009-9246-0
the DIARETDB1 diabetic retinopathy database and evaluation protocol, Procedings of the British Machine Vision Conference 2007, pp.61-65, 2007. ,
DOI : 10.5244/C.21.15
Invariant image recognition by zernike moments. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.12, issue.5 101, pp.489-497, 1990. ,
DOI : 10.1109/34.55109
Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching, IEEE Transactions on Medical Imaging, vol.20, issue.11, pp.1193-1200, 2001. ,
DOI : 10.1109/42.963823
Blood vessel tracking technique for optic nerve localisation for field 1-3 color fundus images, Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on, pp.1437-1441, 2003. ,
Geodesic methods in quantitative image analysis, Pattern Recognition, vol.17, issue.2, pp.177-187, 1984. ,
DOI : 10.1016/0031-3203(84)90057-8
Analyse automatique des images angiofluorographiques au cours de la rétinopathie diabétique, p.62, 1983. ,
Microaneurysm detection in retinal images using a rotating cross-section based model, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1405-1409, 2011. ,
DOI : 10.1109/ISBI.2011.5872663
Conformational analysis of protein structures derived from NMR data, Proteins: Structure, Function, and Genetics, vol.231, issue.3, pp.232-251, 1993. ,
DOI : 10.1002/prot.340170303
A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features, IEEE Transactions on Medical Imaging, vol.30, issue.1, pp.146-158, 2011. ,
DOI : 10.1109/TMI.2010.2064333
Automated three stage red lesions detection in digital color fundus images, WSEAS Transactions on Computers, vol.7, issue.4, pp.207-215, 2008. ,
Rétinopathie diabétique, p.13, 2010. ,
OPHDIAT??: A telemedical network screening system for diabetic retinopathy in the ??le-de-France, Diabetes & Metabolism, vol.34, issue.3, pp.227-234, 2008. ,
DOI : 10.1016/j.diabet.2007.12.006
Contrasts and activity lattice, Signal Processing, vol.16, issue.4, pp.303-317, 1989. ,
DOI : 10.1016/0165-1684(89)90028-5
Automated microaneurysm detection method based on double ring filter in retinal fundus images, Medical Imaging 2009: Computer-Aided Diagnosis, pp.72601-72601, 2009. ,
DOI : 10.1117/12.813468
Automatic detection of red lesions in digital color fundus photographs, IEEE Transactions on Medical Imaging, vol.24, issue.5, pp.584-592, 2005. ,
DOI : 10.1109/TMI.2005.843738
Automated Detection and Differentiation of Drusen, Exudates, and Cotton-Wool Spots in Digital Color Fundus Photographs for Diabetic Retinopathy Diagnosis, Investigative Opthalmology & Visual Science, vol.48, issue.5, pp.2260-2267, 2007. ,
DOI : 10.1167/iovs.06-0996
Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs, IEEE Transactions on Medical Imaging, vol.29, issue.1, pp.185-195, 2010. ,
DOI : 10.1109/TMI.2009.2033909
URL : https://hal.archives-ouvertes.fr/hal-00473901
Differential Area Profiles, 2010 20th International Conference on Pattern Recognition, pp.1533-1548, 2012. ,
DOI : 10.1109/ICPR.2010.993
URL : http://publications.jrc.ec.europa.eu/repository/handle/JRC59387
A new approach for the morphological segmentation of high-resolution satellite imagery. Geoscience and Remote Sensing, IEEE Transactions on, vol.39, issue.2, pp.309-320, 2001. ,
The efficacy of automated "disease/no disease" grading for diabetic retinopathy in a systematic screening programme, British Journal of Ophthalmology, vol.91, issue.11, pp.1512-1517, 2007. ,
DOI : 10.1136/bjo.2007.119453
An Integrated Approach Using Automatic Seed Generation and Hybrid Classification for the Detection of Red Lesions in Digital Fundus Images, 2008 IEEE 8th International Conference on Computer and Information Technology Workshops, pp.462-467, 2008. ,
DOI : 10.1109/CIT.2008.Workshops.35
Optimal Wavelet Transform for the Detection of Microaneurysms in Retina Photographs, IEEE Transactions on Medical Imaging, vol.27, issue.9, pp.1230-1241, 2008. ,
DOI : 10.1109/TMI.2008.920619
URL : https://hal.archives-ouvertes.fr/hal-00326135
Adaptive Nonseparable Wavelet Transform via Lifting and its Application to Content-Based Image Retrieval, IEEE Transactions on Image Processing, vol.19, issue.1, pp.25-35, 2010. ,
DOI : 10.1109/TIP.2009.2030479
URL : https://hal.archives-ouvertes.fr/hal-00473899
A multiple-instance learning framework for diabetic retinopathy screening, Medical Image Analysis, vol.16, issue.6, 2012. ,
DOI : 10.1016/j.media.2012.06.003
URL : https://hal.archives-ouvertes.fr/hal-00786539
Studying disagreements among retinal experts through image analysis, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.5959-5962, 2012. ,
DOI : 10.1109/EMBC.2012.6347351
URL : https://hal.archives-ouvertes.fr/hal-00782745
Weakly supervised classification of medical images, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.110-113, 2012. ,
DOI : 10.1109/ISBI.2012.6235496
URL : https://hal.archives-ouvertes.fr/hal-00782750
Automated feature extraction for early detection of diabetic retinopathy in fundus images, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.210-217, 2009. ,
DOI : 10.1109/CVPR.2009.5206763
Multiscale image analysis and modeling using rank order based filters -application to defect detection, p.20, 1991. ,
Antiextensive connected operators for image and sequence processing, IEEE Transactions on Image Processing, vol.7, issue.4, pp.555-570, 1998. ,
DOI : 10.1109/83.663500
Retinal image analysis based on mixture models to detect hard exudates, Medical Image Analysis, vol.13, issue.4, pp.650-658, 2009. ,
DOI : 10.1016/j.media.2009.05.005
Improving hard exudate detection in retinal images through a combination of local and contextual information, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.5-8, 2010. ,
DOI : 10.1109/ISBI.2010.5490429
Contextual computer-aided detection: Improving bright lesion detection in retinal images and coronary calcification identification in CT scans, Medical Image Analysis, vol.16, issue.1, pp.50-62, 2012. ,
DOI : 10.1016/j.media.2011.05.004
Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images, Medical Imaging 2009: Computer-Aided Diagnosis, p.63, 2009. ,
DOI : 10.1117/12.812088
Cost-effectiveness of implementing automated grading within the national screening programme for diabetic retinopathy in Scotland, British Journal of Ophthalmology, vol.91, issue.11, pp.1518-1523, 2007. ,
DOI : 10.1136/bjo.2007.120972
Segmentation of elongated objects using attribute profiles and area stability, Pattern Recognition, p.24, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01101643
Image analysis and mathematical morphology, 1921. ,
Automated detection of diabetic retinopathy on digital fundus images, Diabetic Medicine, vol.97, issue.2, pp.105-112, 2002. ,
DOI : 10.1046/j.1464-5491.2002.00613.x
Morphological image analysis: principles and applications, 1921. ,
Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods, Computerized Medical Imaging and Graphics, vol.32, issue.8, pp.720-727, 2008. ,
DOI : 10.1016/j.compmedimag.2008.08.009
Automatic Exudate Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering, Sensors, vol.9, issue.3, pp.2148-2161, 2009. ,
DOI : 10.3390/s90302148
URL : http://doi.org/10.3390/s90302148
An Image-Processing Strategy for the Segmentation and Quantification of Microaneurysms in Fluorescein Angiograms of the Ocular Fundus, Computers and Biomedical Research, vol.29, issue.4, pp.284-302, 1996. ,
DOI : 10.1006/cbmr.1996.0021
Ridge-Based Vessel Segmentation in Color Images of the Retina, IEEE Transactions on Medical Imaging, vol.23, issue.4, pp.501-509, 2004. ,
DOI : 10.1109/TMI.2004.825627
Grayscale morphology Computer Vision, Graphics, and Image Processing, pp.333-355, 1986. ,
Microaneurysm detection in colour fundus images, Image Vision Comput. New Zealand, pp.280-284, 2003. ,
Splat Feature Classification With Application to Retinal Hemorrhage Detection in Fundus Images, IEEE Transactions on Medical Imaging, vol.32, issue.2, p.84, 2013. ,
DOI : 10.1109/TMI.2012.2227119
Detection of Anatomic Structures in Human Retinal Imagery, IEEE Transactions on Medical Imaging, vol.26, issue.12, pp.1729-1739, 2007. ,
DOI : 10.1109/TMI.2007.902801
A fuzzy vessel tracking algorithm for retinal images based on fuzzy clustering, IEEE Transactions on Medical Imaging, vol.17, issue.2, pp.263-273, 1998. ,
DOI : 10.1109/42.700738
Automated detection of diabetic retinopathy in digital retinal images: a tool for diabetic retinopathy screening, Diabetic Medicine, vol.98, issue.1, pp.84-90, 2004. ,
DOI : 10.1046/j.1464-5491.2002.00613.x
Efficient computation of various types of skeletons, Medical Imaging V: Image Processing, pp.297-311, 1991. ,
Segmentation of Color Fundus Images of the Human Retina: Detection of the Optic Disc and the Vascular Tree Using Morphological Techniques, Medical Data Analysis, pp.282-287, 2001. ,
DOI : 10.1007/3-540-45497-7_43
A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina, IEEE Transactions on Medical Imaging, vol.21, issue.10, pp.1236-1243, 2002. ,
DOI : 10.1109/TMI.2002.806290
Automatic detection of microaneurysms in color fundus images, Medical Image Analysis, vol.11, issue.6, pp.555-572, 2007. ,
DOI : 10.1016/j.media.2007.05.001
Object count/area graphs for the evaluation of object detection and segmentation algorithms, International Journal of Document Analysis and Recognition (IJDAR), vol.6, issue.4, pp.280-296, 2006. ,
DOI : 10.1007/s10032-006-0014-0
On the Adaptive Detection of Blood Vessels in Retinal Images, IEEE Transactions on Biomedical Engineering, vol.53, issue.2, pp.341-343, 2006. ,
DOI : 10.1109/TBME.2005.862571
Algorithm for detecting micro-aneurysms in low-resolution color retinal images, p.63, 2001. ,
Comparative study of contrast enhancement and illumination equalization methods for retinal vasculature segmentation, Proc. Cairo Int, pp.21-24, 2006. ,
Detection of microaneurysms using multi-scale correlation coefficients, Pattern Recognition, vol.43, issue.6, pp.2237-2248, 2010. ,
DOI : 10.1016/j.patcog.2009.12.017
Top-down and bottom-up strategies in lesion detection of background diabetic retinopathy, Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, pp.422-428, 2005. ,
Retinal Spot Lesion Detection Using Adaptive Multiscale Morphological Processing, Advances in Visual Computing, pp.490-501, 2006. ,
DOI : 10.1007/11919629_50
application of the morphological ultimate opening to the detection of microaneurysms on eye fundus images from clinical databases, ICS, vol.63, p.108, 2011. ,
Automatic detection of exudates in color retinal images, p.108, 2012. ,
Procédé de normalisation déchelle d'images ophtalmologiques (patent, filing number: 12 53929), pp.2012-108 ,
Spatial normalization of eye fundus images, International Symposium on Biomedical Imaging -ISBI. IEEE, p.108, 2012. ,
URL : https://hal.archives-ouvertes.fr/hal-00945417
Exudate detection in color retinal images for mass screening of diabetic retinopathy, Medical Image Analysis, vol.18, issue.7, p.108, 2014. ,
DOI : 10.1016/j.media.2014.05.004
URL : https://hal.archives-ouvertes.fr/hal-01082809
Contrast limited adaptive histogram equalization In Graphics gems IV, pp.474-485, 1994. ,