« Previous
Next »
Medical Engineering & Physics
Volume 30, Issue 3
, Pages 350-357
, April 2008
A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis
References
- . Screening for diabetic retinopathy. Ann Intern Med. 1992;116(8):660–671
- . The preprocessing of retinal images for the detection of fluorescein leakage. Phys Med Biol. 1999;44(1):293–308
- . Colour normalisation to reduce inter-patient and intra-patient variability in microaneurysm detection in colour retinal images. In: Proceedings of the APRS Workshop on Digital Image Computing, vol. 163. 2005;p. 8
- . Luminosity and contrast normalization in retinal images. Med Image Anal. 2003;9(3):179–190
- . Mapping the human retina. IEEE Trans Med Imaging. 1998;17(4):606–619
- Retinal image analysis: concepts, applications and potential. Prog Retin Eye Res. 2006;25(1):99–127
- . A computer method of understanding ocular fundus images. Pattern Recognition. 1982;15(6):431–443
- . A image processing system for analyzing color fundus photographs with regard to diabetic retinopathy. Klinische Monatsblatter für Augenheilkunde. 1997;211:11
- . Automated feature extraction in color retinal images by a model based approach. IEEE Trans Biomed Eng. 2004;51(2):246–254
- . Automated detection and quantification of retinal exudates. Graefe's Archive for Clinical and Experimental Ophthalmology. 1993;231(2):90–94
- . 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(10):1236–1243
- . Image analysis of fundus photographs—the detection and measurement of exudates associated with diabetic retinopathy. Ophthalmology. 1989;96:80–86
- Hybrid fuzzy image processing for situation assessment: a knowledge-based system for early detection of diabetic retinopathy. IEEE Eng. Med. Biol. Mag. 2000;19(1):76–83
- . ADRIS: an automatic diabetic retinal image screening system. In: Cios KJ editors. Medical data mining and knowledge discovery. New York: Springer-Verlag; 2000;p. 181–210
- . An effective approach to detect lesions in color retinal images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recogniton. 2000;p. 181–186
- . Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. Br J Ophthalmol. 1996;80(11):940–944
- Osareh A. Automated identification of diabetic retinal exudates and the optic disc. Ph.D. thesis. Bristol; 2004.
- . Fundamentals of digital image processing. New York: Prentice Hall; 1989;
- . Morphological operators for image sequences. Computer Vision and Image Understanding. 1995;62:326–346
- . Statistical pattern recognition. New York: Academic Press; 1990;
- . Fast boundary detection: a generalization and a new algorithm. IEEE Transactions on Computers. 1977;26(10):988–998
- . Neural network for pattern recognition. Oxford: Clarendon Press; 1997;
- . Morphological image analysis: principles and applications. New York: Springer-Verlag; 1999;
- . Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Trans Med Imaging. 1989;8(3):263–269
- . The FROC, AFROC and DROC variants of the ROC analysis. In: Beutel J, Kundel HL, Van Metter RL editor. Handbook of medical imaging. vol. 1:Bellingham: SPIE; 2000;p. 771–798
- . Retinal photography screening for diabetic eye disease. London: British Academic Association; 1997;
PII: S1350-4533(07)00067-7
doi: 10.1016/j.medengphy.2007.04.010
© 2007 IPEM. Published by Elsevier Inc. All rights reserved.
« Previous
Next »
Medical Engineering & Physics
Volume 30, Issue 3
, Pages 350-357
, April 2008
