Decision support for automated screening of diabetic retinopathy

Conference Record - Asilomar Conference on Signals, Systems and Computers

Volumn 2, Issue , 2004, Pages 1630-1634

  Kahai, Pallavi ^a   Namuduri, Kamesh Rao ^a   Thompson, Hilary ^b  

^a WICHITA STATE UNIVERSITY   (United States)

^b LSU EYE CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIABETIC PATIENTS; DIABETIC RETINOPATHY; INTRA-RETINAL MICROVASCULAR ABNORMALITIES (IRMA); MICROANEURYSMS;

ALGORITHMS; DATABASE SYSTEMS; DECISION SUPPORT SYSTEMS; DIAGNOSIS; EDGE DETECTION; PROBABILITY;

DISEASES;

EID: 21644467876     PISSN: 10586393     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. R. Klein, D. Fong, L. Aiello, T. Gardner, G. King, G. Blankenship, and et al, "Retinopathy in diabetes," Diabetes Care, Jan 2004.
2. R. Klein, B. Klein, S. Moss, M. Davis, and D. DeMets, "The Wisconsin epidemiologic study of diabetic retinopathy. ii. prevalnence and risk of diabetic retinopathy when age at diagnosis is less than 30 years," Arch Ophthalmol, vol. 102, pp. 520-26, 1984.
3. H. Buch, T. Vinding, and N. Nielsen, "Prevalence and causes of visual impairment according to world health organization and united states criteria in an aged, urban Scandinavian population: the Copenhagen city eye study," Ophthalmology, vol. 108, no. 12, pp. 2347-57, Dec 2001.
4. K. Namuduri, H. Thompson, and M. Hartnett, "A multiscale-multiresolution method for automated retinal feature detection, " Association for Research in Vision and Ophthalmology (ARVO) Conference, May 2003.
5. B. Ege, O. Hejlesen, O. Larsen, K. Moller, B. Jennings, and et al, "Screening for diabetic retinopathy using computer based image analysis and statistical classification," Comput Methods Programs Biomed, vol. 62, no. 3, pp. 165-75, Jul 2000.
6. G. Boucher, "Development of an image analysis software to assist in the diagnostic of diabetic retinopathy," In Proceedings of the 5th Conference on the Medical Aspect of Telemedicine, Oct 2000.
7. A. Osareh, M. Mirmehdi, B. Thomas, and R. Markham, "Comparative exudate classification using support vector machines and neural networks," 5th International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2002.
8. R. Markham, A. Osareh, M. Mirmehdi, B. Thomas, and M. Macipe, "Automated identification of diabetic retinal exudates using support vector machines and neural networks," Department of Computer Science, University of Bristol, Bristol, United Kingdom; Bristol Eye Hospital, Bristol, United Kingdom, May 2003.
9. C. Serurys, D. Brahmi, A. Giron, N. Cassoux, R. Triller, and B. F. P. LeHuang, "A learning by sample approach for the detection of features in medical images," ANNIMAB Society, May 2000.
10. M. Lopez, C. Sanchez, and R. Hornero, "Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy," Ioba, University of Valladolid, Valladolid, Spain, May 2003.
11. H. Poor, An Introduction to Signal Detection and Estimation. Springer Publication, 1994.
12. R. Duda, P. Hart, and D. Stork, Pattern Classification. Wiley Interscience Publication, 2001.