Abstract
In this paper, the learning algorithm of networks is discussed. The programming example of 3-layer BP networks is given with Visual C++6.0 program langue. Based on this model, a lung cancer intelligent diagnosis system is successfully implemented. Furthermore, the paper introduces network’s structure design, preferences and the source of sample datum in factual applications. The ameliorative arithmetic is applied to the study of networks and BP dynamic evolving process is designed. The experiments indicate cell images are recognized and classified by the trained neural network. The study illustrates the system has feasibility and clinical value in lung cancer diagnosis.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning Internal Representations by Error Propagation. In: Rumelhart, D.E., McClelland, J.L. (eds.) Parallel distributed processing: exploration in the microstructure of cognition. Foundations, vol. 1, The MIT press, Cambridge (1986)
Falchini, M., Stecco, A.L.: Carmigalni: Neural Network Based Detection of Pulmonary Nodules on Chest Radiographs. Radio Med (Torino) 98, 259–263 (1999)
Nakamura, K., Yoshida, H., Engellmann, R.: Computerized Analysis of the Likelihood of Malignancy in Solitary Pulmonary Nodules with Use of Artificial Neural Networks. Radiology 214, 823–830 (2000)
Hagan, M.T., Demuth, H.B., Beale, M.H.: Neural Network Design, pp. 232–235. China machine press, Beijing (2002)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, pp. 34–75. Publishing House of electronics industry, Beijing (2003)
Zheng, N.: Computer Vision and Pattern Recognition, pp. 8–9. Publishing House of Defence Industry, Beijing (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, X., Tang, Z., Sun, C. (2005). Study of BP Neural Network and Its Application in Lung Cancer Intelligent Diagnosis. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_123
Download citation
DOI: https://doi.org/10.1007/11427469_123
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
eBook Packages: Computer ScienceComputer Science (R0)