A Novel Approach to Diagnose Diabetes Based on the Fractal Characteristics of Retinal Images

IEEE Transactions on Information Technology in Biomedicine

Volumn 7, Issue 3, 2003, Pages 163-170

  Cheng, Shu Chen ^a   Huang, Yueh Min ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Backpropagation algorithm; Classification; Diagnosis system; Fractal dimension; Genetic algorithm; Image processing; Lacunarity; Radial basis function network; Voting scheme

Indexed keywords

GENETIC ALGORITHMS; IMAGE PROCESSING; IMAGE QUALITY; METABOLISM; PROBABILITY; RADIAL BASIS FUNCTION NETWORKS; VISION;

BACKPROPAGATION ALGORITHMS; DIAGNOSIS SYSTEMS; FRACTAL DIMENSION; LACUNARITY; VOTING SCHEME;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; DIABETES MELLITUS; DIABETIC RETINOPATHY; EVALUATION; FRACTAL ANALYSIS; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; OPHTHALMOSCOPY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; VALIDATION STUDY;

ALGORITHMS; DIABETES COMPLICATIONS; DIABETES MELLITUS; DIABETIC RETINOPATHY; FRACTALS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; OPHTHALMOSCOPY; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 0142244288     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2003.813792     Document Type: Article

References (17)

1. J. J. Kanski, Clinical Ophthalmology, 3rd ed. London, U.K.: Butter-worth-Heinemann, 1993, pp. 344-347.
2. R. C. Gonzales and R. E. Woods, Digital Image Processing. Reading, MA: Addison-Wesley, 1992, pp. 455-456.
3. H. O. Peitgen, H. Jurgens, and D. Saupe, Chaos and Fractals: New Frontiers of Science. Berlin, Germany: Springer-Verlag, 1992, pp. 202-213.
4. S. Nakamura, Applied Numerical Methods in C. Englewood Cliffs, NJ: Prentice-Hall, 1993, pp. 294-296.
5. J. Fender, Fractals. New York: Plenum, 1988, pp. 62-65.
6. B. B. Mandelbrot, The Fractal Geometry of Nature New York, 1983, pp. 14-19, 310-318.
7. R. Rojas, Neural Networks: A Systematic Introduction. Berlin, Germany: Springer, 1996, pp. 149-162.
8. S. Haykin, Neural Networks, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1999, pp. 161-175.
9. J. A. Anderson, An Introduction to Neural Networks. Cambridge, MA: MIT Press, 1995, pp. 255-277, 454-459.
10. L. Fu, Neural Networks in computer Intelligence. New York: McGraw-Hill, 1994, pp. 80-96.
11. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, 3rd ed. Berlin, Germany: Springer, 1999, pp. 97-106.
12. G. Winter, J. Periaux, M. Galan, and P. Cuesta, Genetic Algorithms in Engineering and Computer Science. New York: Wiley, 1995, pp. 203-213.
13. M. Mitchell, An Introduction to Genetic Algorithms, 3rd ed. Cambridge, MA: MIT Press, 1997, pp. 65-79.
14. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Trans. Syst., Man, Cybern., vol. 22, no. 3, pp. 418-435, 1992.
15. J. Y. Lee, H. Y. Youn, and A. D. Singh, "Adaptive unanimous voting (UV) scheme for distributed self-diagnosis," IEEE Trans. Comput., vol. 44, no. 5, pp. 730-735, 1995.
16. R. Candela, G. Mirelli, and R. Schifani, "PD recognition by means of statistical and fractal parameters and a neural network," IEEE Trans. Dielect. Elect. Insulation, vol. 7, no. 1, pp. 87-94, 2000.
17. A. I. Penn and M. H. Loew, "Estimating fractal dimension of medical images," in Proc. SPIE Medical Imaging 1996: Image Processing, vol. 2710, 1996, pp. 840-851.