Abstract
Intelligent algorithm is simulated biological theory of intelligent systems constitute a new type of information processing technology, has been widely used in industrial engineering, information processing and other fields. In recent years, in the field of image processing and analysis, intelligent algorithms are also widely used technology. In this paper, intelligent algorithm technique in medical image segmentation, image registration and the application of computer-aided technology and research are reviewed, representative described techniques and algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bianchini, M., Frasconi, P.: Learning Without Local Minima in Radial Basis Function Networks. IEEE Transaction on Neural Networks 6(3), 749–756 (1995)
Li, S.-R., Ebong, I.E.: Tunneling-Based Cellular Nonlinear Network Architectures for Image Processing. IEEE (2009)
Suzuki, K., Li, F., Sone, S., et al.: Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network. IEEE Trans. Med. Image 24(9), 1138–1150 (2005)
Babaguchi, N., et al.: Connectionist model binarization. In: Proc. 10th ICPR, pp. 51–56 (1990)
Joo, S., Moon, W.K., Kim, H.C.: 26th Annual International Conference of the IEEE EMBS (2004)
Satirapod, C., Trisirisatayawong, I., Homniam, P.: Establishing Ground Control Points for High-resolution Satellite Imagery Using GPS Precise Point Positioning. In: Proceedings of 2003 IEEE International Geo Sciences and Remote Sensing Symposium, IGARSS 2003, July 21-25, vol. 7, pp. 4486–4488 (2003)
Cascio, D., Fauci, F., Magro, R., et al.: Mammogram segmentation by contour searching and mass lesions classification with neural network. IEEE Transactions on Nuclear Science 53(5), 2827–2833 (2006)
Papadopoulos, A., Fotiadisb, D.I., Likas, A.: Anautomatic microcal-cification detection system based on a hybrid neural network classifier. Artif. Intell. Med. 25(2), 149–167 (2002)
Dunstone, E., Andrew, J.: Super-high, scale invariant image compression using a surface learning neural network. In: International Symposium on Speech (1994)
Cortes, C., et al.: A network system for image segmentation. In: Proc. Intl. Joint Conf. on Neural Network, vol. 1, pp. 121–125 (1989)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag GmbH Berlin Heidelberg
About this paper
Cite this paper
Zhang, J. (2012). Natural Computing and Intelligent Algorithms in Materials Image Processing Technology. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29390-0_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-29390-0_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29389-4
Online ISBN: 978-3-642-29390-0
eBook Packages: EngineeringEngineering (R0)