P. J. Kertes and T. M. Johnson, Evidence-based eye care, 2007.

A. Joussen, T. Gardner, T. , and B. Kirchhof, Retinal vascular disease [3] St. luke's retinal cataract and laser institute, 2007.

D. E. Singer, D. M. Nathan, H. A. Fogel, and A. P. Schachat, Screening for Diabetic Retinopathy, Annals of Internal Medicine, vol.116, issue.8, pp.660-671, 1992.
DOI : 10.7326/0003-4819-116-8-660

S. Parmet, Age-Related Macular Degeneration, JAMA, vol.295, issue.20, 2001.
DOI : 10.1001/jama.295.20.2438

P. Saine, Fundus photography: What is a fundus camera, In Ophthalmic Photographers Society, 2006.

N. Patton, T. M. Aslam, T. Macgillivray, I. J. Deary, B. Dhillon et al., Retinal image analysis: concepts, applications and potential, Progress in Retinal and Eye Research, pp.99-127, 2006.
DOI : 10.1016/j.preteyeres.2005.07.001

L. Giancardo, M. Abramoff, E. Chaum, T. Karnowski, F. Meriaudeau et al., Elliptical local vessel density: A fast and robust quality metric for retinal images, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008.
DOI : 10.1109/IEMBS.2008.4649968

F. Zana and J. C. Klein, Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation, IEEE Transactions on Image Processing, pp.1010-1019, 2001.
DOI : 10.1109/83.931095

R. C. Gonzalez and E. Richard, Woods, digital image processing, 2002.

A. Youssif, A. Z. Ghalwash, and A. S. Ghoneim, A comparative evaluation of preprocessing methods for automatic detection of retinal anatomy, Proc. 5th Int. Conf. Informatics Syst.(INFOS2007), pp.24-30, 2007.

M. L. Giger, H. P. Chan, and J. Boon, and AAPM, Medical Physics, vol.31, issue.1, pp.5799-5820, 2008.
DOI : 10.1056/NEJMoa066099

L. Giancardo, F. Meriaudeau, T. P. Karnowski, K. W. Tobin-jr, and E. Chaum, Validation of microaneurysm-based diabetic retinopathy screening across retina fundus datasets, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems
DOI : 10.1109/CBMS.2013.6627776
URL : https://hal.archives-ouvertes.fr/hal-00831565

T. J. Quellec, B. Macgillivray, and . Dhillon, Validating retinal fundus image analysis algorithms: Issues and a proposal, Investigative Ophthalmology & Visual Science, p.2013
URL : https://hal.archives-ouvertes.fr/hal-00824593

L. Giancardo, F. Meriaudeau, T. Karnowski, K. Tobin-jr, Y. Li et al., Microaneurysms detection with the radon cliff operator in retinal fundus images, Medical Imaging 2010: Image Processing, p.76230, 2010.
DOI : 10.1117/12.844442

K. Adal, D. Sidibé, S. Ali, T. P. Karnowski, and F. Mériaudeau, Automated Detection of Micro-aneurysms using Blob Analysys and Semi-suêrvised Learning Under correction, IEEE TBME, 2013.

B. Antal and A. Hajdu, 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

I. Lazar, A. Hajdu, and R. Quareshi, Retinal microaneurysm detection based on intensity profile analysis, 8th International Conference on Applied Informatics, 2010.

L. Giancardo, F. Meriaudeau, T. P. Karnowski, Y. Li, S. Garg et al., Exudate-based diabetic macular edema detection in fundus images using publicly available datasets, Medical Image Analysis, vol.16, issue.1, pp.216-226, 2012.
DOI : 10.1016/j.media.2011.07.004
URL : https://hal.archives-ouvertes.fr/hal-00639756

]. S. Ali, K. Adal, D. Sidibé, T. Karnowski, and F. Mériaudeau, Steerable wavelet transform for atlas based retinal lesion segmentation, Medical Imaging 2013: Image Processing, pp.9-14, 2013.
DOI : 10.1117/12.2006357
URL : https://hal.archives-ouvertes.fr/hal-00784561

. Messidor, Methods to evaluate segmentation and indexing techniques in the field of retinal ophthalmology, 2010.

M. Niemeijer, M. D. Abramoff, and B. Van-ginneken, Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs, IEEE Transactions on Medical Imaging, pp.775-785, 2009.
DOI : 10.1109/TMI.2008.2012029

C. I. Sanchez, M. Niemeijer, A. V. Dumitrescu, M. S. Suttorp-schulten, M. D. Abramoff et al., Evaluation of a Computer-Aided Diagnosis System for Diabetic Retinopathy Screening on Public Data, Investigative Opthalmology & Visual Science, vol.52, issue.7, pp.4866-4871, 2011.
DOI : 10.1167/iovs.10-6633

M. Niemeijer, B. Van-ginneken, M. J. Cree, A. Mizutani, G. Quellec et al., 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

T. Kauppi, V. Kalesnykiene, J. Kamarainen, L. Lensu, I. Sorri et al., 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

L. Giancardo, T. Meriaudeau, K. Karnowski, . Tobin, . Favaro et al., Textureless Macula Swelling Detection With Multiple Retinal Fundus Images, IEEE Transactions on Biomedical Engineering, vol.58, issue.3, pp.795-799, 2011.
DOI : 10.1109/TBME.2010.2095852
URL : https://hal.archives-ouvertes.fr/hal-00580706

T. Lindeberg, Feature detection with automatic scale selection, International Journal of Computer Vision, vol.30, issue.2, pp.79-116, 1998.
DOI : 10.1023/A:1008045108935

H. Bay, A. Ess, T. Tuytelaars, and L. Van-gool, Speeded-Up Robust Features (SURF), Computer Vision and Image Understanding, vol.110, issue.3, pp.346-359, 2008.
DOI : 10.1016/j.cviu.2007.09.014
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.738

A. Fazlollahi, P. Bourgeat, F. Meriaudeau, L. Giancardo, V. L. Villemagne et al., Automatic Detection of Cerebral Microbleed in SWI using Radon Transform, ISMRM, pp.20-26, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00834775