Abstract
In this paper medical applications of supervised and unsupervised neural networks image processing algorithms are presented and discussed by means of quantitative experimental results in the field of radiotherapy. The investigated case study concerns the problems and the consequent solutions referred to the two phases of the treatment plan necessary after the quadrantectomy of a cohort of patients affected by breast cancer.
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References
Vitoantonio, B., Giuseppe, M., Giuseppe, P.: Evolutionary Approach to Inverse Planning in Coplanar Radiotherapy. Image Vision Comput. 25(2), 196–203 (2007)
Vitoantonio, B., Giuseppe, M., Mario, M.: A Neural Network Approach to Medical Image Segmentation and Three-Dimensional Reconstruction. ICIC (1), 22–31 (2006)
Knowles, J., Corne, D., Bishop, M.: Evolutionary Training of Artificial Neural Networks for Radiotherapy Treatment of Cancers. In: Proceedings of IEEE International Conference on Evolutionary Computation, Alaska, pp. 398-403 (1998)
Timp, S., Karssemeijer, N.: A New 2D Segmentation Method Based on Dynamic Programming Applied to Computer Aided Detection in Mammograph. Medical Physics 31, 958–971 (2004)
Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn. Prentice-Hall, Englewood Cliffs
Kohonen, T.: Self-Organization and Associative Memory. Springer, Heidelberg (1988)
Wei, J.K., George, A.S., Hsi, W.C., Ringor, M., Lu, X.Y.: Dosimetric Impact of a CT Metal Artifact Suppression Algorithm for Proton, Electron and Photon Therapies Jikun Wei et al Phys. Med. Biol. 51, 5183-5197 (2006)
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Bevilacqua, V. et al. (2007). Metallic Artifacts Removal in Breast CT Images for Treatment Planning in Radiotherapy by Means of Supervised and Unsupervised Neural Network Algorithms. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_138
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DOI: https://doi.org/10.1007/978-3-540-74171-8_138
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74170-1
Online ISBN: 978-3-540-74171-8
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