Automatic classification of prostate cancer using pseudo-gaussian radial basis function neural network

ESANN 2005 Proceedings - 13th European Symposium on Artificial Neural Networks

Volumn , Issue , 2007, Pages 145-150

  Valenzuela, O ^a   Rojas, I ^a   Rojas, F ^a   Marquez, L ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC CLASSIFICATION; AUTOMATIC PROCEDURES; CLASSIFICATION RATES; FEATURE SUBSET SELECTION; IMAGE INTERPRETATION; IMAGE PROCESSING TECHNIQUE; RADIAL BASIS FUNCTION NEURAL NETWORKS; SOFTCOMPUTING TECHNIQUES;

IMAGE PROCESSING; NEURAL NETWORKS;

DISEASES;

EID: 84886998444     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. www. cancer. org, "Cancer Statistics 2004", downloaded on 4th April, 2004. www. prostate. com/
2. U Patel, TRUS and prostate biopsy: current status, Prostate Cancer and prostatic diseases. ISSN 1365-7852, vol. 7, pp. 208-210, Septermber, 2004
3. M. Lujan, A. Paez, C. Santonja, T. Pascual, I. Fernandez & A. Berenguer, "Prostate cancer detection and tumor characteristics in men with multiple biopsy sessions" Prostate Cancer and prostatic diseases, vol. 7, pp. 238-242, Septermber, 2004
4. G. A. Babich and O. I. Camps, "Weighted Parzen Window for Pattern Classification," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 5, pp. 567-570, May 1996.
5. K. Fukunaga and R. R. Hayes, "The Reduced Parzen Classifier," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 4, pp. 423-425, Apr. 1989.
6. Nojun Kwak, Chong-Ho Choi, "Input Feature Selection by Mutual Information Based on Parzen Window, IEEE Trans. Pattern Analysis and Mach. Intelligence,vol. 24, no. 12, pp. 1667-1671, 2002.
7. H. Akaike, "Information theory and extension of the maximum likelihood principle", Akademia Kiado, Budapest, pp. 267-810, 1973.
8. C. M. Bishop, "Neural Networks for Pattern Recognition", Clarendon Press, Oxford, 1995.
9. N. B. Karayiannis, G. Weiqun Mi, "Growing Radial Basis Neural Networks: Merging Supervised and Unsupervised Learning with Network Growth Techniques", IEEE Transaction on Neural Networks, vol. 8, no. 6, pp. 1492-1506, November 1997.
10. I. Rojas, H. Pomares, J. L. Bernier, J. Ortega, B. Pino, F. J. Pelayo, A. Prieto, "Time series analysis using normalized PG-RBF network with regression weights", Neurocomputing, vol. 42 (2002)267-285