References
[1]. M. R. Hee, C. A. Puliafito, C. Wong, J. S. Duker, E.
Reichel, B. Rutledge, J. S. Schuman, E. A. Swanson, and J.
G. Fujimoto,(1995). "Quantitative assessment ofmacular
edema with optical coherence tomography," Arch.
Ophthalmol., Vol. 113, No. 8, pp. 1019–1029.
[2].R.F.N. Silberman, K. Ahlrich, and L. Subramanian,(
2010). "Case for automated detection of diabetic
retinopathy," Proc. AAAI Artif. Intell. Development (AID'
10), pp. 85–90.
[3]. K. Sai Deepak and Jayanthi Sivasamy,(2012).
"Automatic Assessment of Macular Edema From Color Retinal Images," IEEE Transactions on Biomedical
Engineering, Vol. 31, No. 3, pp. 766-776.
[4]. J. Davidson, T. Ciulla, J. McGill, K. Kles, and P.
Anderson,(2007). "How the diabetic eye loses vision,"
Endocrine, Vol. 32, pp. 107–116.
[5]. C. P. Wilkinson, F. L. Ferris, R. E. Klein, P. P. Lee, C. D.
A g a r d h , M . D a v i s , D . D i l l s , A . K a m p i k , R .
Pararajasegaram, and J. T. Verdaguer,(2003). "Proposed
international clinical diabetic retinopathy and diabetic
macular edema disease severity scales," Am. Acad.
Ophthalmol., Vol. 110, No. 9, pp. 1677–1682.
[6]. NIH. (2009). Facts about diabetic retinopathy disease
[nei health information]. http://www.nei.nih.gov/health/
diabetic/retinopathy.asp
[7]. Zhang, X., and Chutatape, O. (2005). Top-down and
bottom-up strategies in lesion detection of background
diabetic retinopathy.In CVPR '05: Proceedings of the
2005 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (CVPR'05) - Volume 2,
422–428. Washington, DC, USA: IEEE Computer Society.
[8]. L. Giancardo, F. Meriaudeau, T. P. Karnowski, Y. Li, K. W.
Tobin,Jr., and E. Chaum,(2011). "Automatic retina
exudates segmentation without a manually labelled
training set,"in Proc. 2011 IEEE Int. Symp. Biomed. Imag:
From Nano to Macro, pp. 1396–1400.
[9]. Y.Hatanaka, T. Nakagawa, Y. Hayashi, Y. Mizukusa, A.
Fujita, M.Kakogawa, K.K.M. D. , T. Hara, and H.
Fujita,(2009). "Cad scheme to detect hemorrhages and
exudates in ocular fundus images," in Proc. SPIE Med.
Imag. 2007: Comput.-Aided Diagn., Vol. 6514, pp.
2M1–2M8.
[10]. O. R. Mitchell, C. R. Myers and W. Boyne,(1977). "A
max–min measure for image texture analysis," IEEE
Transactions on Computers, C-2 (4), 408–414.
[11]. A. Osareh, B. Shadgar, and R. Markham,(2009). "A
computational-intelli-gence-based approach for
detection of exudates in diabetic retinopathy images,"
IEEE Trans. Inf. Technol. Biomed., Vol. 13, No. 4, pp.
535–545.
[12]. R. Gonzalez and R. Woods,(1992). Digital Image
Processing. Reading, MA:Addison-Wesley.
[13]. C.Sinthanayothin,(1999). "Image analysis for
automatic diagnosis of diabetic Retinopathy," Ph.D.
dissertation, King's College of London, London,U.K.
[14]. Y. Lim and S. Lee,(1990). "On the color image
segmentation algorithm based on the thresholding and
the fuzzy c-means techniques," Pattern Recogn., Vol. 23,
No. 9, pp. 935–952, 1990.
[15]. C. Bishop,(1995). Neural Networks for Pattern
Recognition. London, U.K.: Oxford Univ. Press.
[16]. L Vincent,(1993). "Morphological grayscale
reconstruction in image analysis: applications and
efficient algorithms," IEEE Journal of Image Processing,
Vol. 2, No. 2, pp. 176–201.
[17]. R A Kirsch,(1971). "Computer determination of the
constituent structure of biological images.," Computers
and Biomedical Research, Vol. 4, No. 3, pp. 315–328, Jun
1971.
[18]. G Quellec, M Lamard, P M Josselin, G Cazuguel, B
Cochener,and C Roux,(2008). "Optimal wavelet
transform for the detection of microaneurysms in retina
photographs," IEEE Trans on Medical Imaging,Vol. 27,No.
9, pp. 1230–1241.
[19]. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J.
Graham,(1995). "Active shape models-Their training and
application," Comput. Vis. Image Understanding, Vol. 61,
No. 1, pp. 38–59.
[20]. H. Li and O. Chutatape,(2003). "A model-based
approach for automated feature extraction in fundus
images," in Proc. 9th IEEE Int. Conf. Comput. Vis., Vol. 1, pp.
394–399.
[21]. C I Sanchez, M Garcia, A Mayo, M I Lopez, and R
Hornero,(2009). "Retinal image analysis based on mixture
models to detect hard exudates.," Medical Image
Analysis,Vol. 13, No. 4, pp. 650–658.
[22]. Akara Sopharak, Bunyarit Uyyanonvara, Sarah
Barman, and Thomas H Williamson,(2008). “Automatic
detection of diabeticretinopathy exudates from non-dilated retinal images using mathematical morphology methods.," Computerized Medical Imaging and
Graphics, Vol. 32, No. 8, pp. 720–727.
[23]. K. Ram and J. Sivaswamy,(2009). "Multi-space
clustering for segmentation of exudates in retinal color
photographs," in Proc. Annu. Int. Conf. IEEE Eng. Med.
Biol. Soc.,pp. 1437–1440.
[24]. G. D. Joshi, J. Sivaswamy, K. Karan, and S. R.
Krishnadas,(2010). "Optic disk and cup boundary
detection using regional information," in Proc. Int. Conf.
Image Process., pp. 948–951.
[25].MESSIDOR, Jun. [Online]. Available: http://messidor.
crihan.fr/index-en php.