A hybrid system for nodal involvement assessment in breast cancer patients

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 2, Issue , 2002, Pages 1049-1050

  Seker, H ^a   Odetayo, M O ^a   Petrovic, D ^a   Naguib, R N G ^a   Bartoli, C ^b   Alasio, L ^b   Lakshmi, M S ^c   Sherbet, G V ^c,d  

^a Faculty of Engineering and Computing   (United Kingdom)

^b Istituto Nazionale per lo Studio   (Italy)

^c NEWCASTLE UNIVERSITY   (United Kingdom)

^d INSTITUTE FOR MOLECULAR MEDICINE   (United States)

Author keywords

Cytometric image analysis; Fuzzy rule based system; Kohonen neural networks; Oncology; Prognosis

Indexed keywords

CYTOLOGY; FEEDFORWARD NEURAL NETWORKS; FUZZY SETS; IMAGE ANALYSIS; KNOWLEDGE BASED SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MULTILAYER NEURAL NETWORKS; ONCOLOGY; PATIENT MONITORING; REGRESSION ANALYSIS; TUMORS;

BREAST CANCER; CYTOMETRIC IMAGE ANALYSIS; KOHONEN NEURAL NETWORKS; NODAL INVOLVEMENT ASSESSMENT; PROGNOSIS;

MEDICAL IMAGING;

EID: 0036906728     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. H. Seker, M. Odetayo, D. Petrovic, R.N.G. Naguib, C. Bartoli, L. Alasio, M.S. Lakshmi and G.V. Sherbet, "Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches", Anticancer Research (International Journal of Cancer Research and Treatment), vol.22(1), pp. 433-438, Jan-Feb. 2002.
2. J.W. Hines, Fuzzy and Neural Approaches in Engineering, John Wiley & Sons, NY, 1997.
3. Y.Q. Zhang and A. Kandel, "Compensatory neurofuzzy systems with fast learning algorithms", IEEE Trans. on Neural Networks, vol. 9, pp. 83-105, 1998.
4. S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice-Hall, 1999.
5. B. Flury, A First Course in Multivariate Statistics, Springer, 1997.