Segmentation of MR and CT images using a hybrid neural network trained by genetic algorithms

Neural Processing Letters

Volumn 16, Issue 3, 2002, Pages 211-225

  Dokur, Zümray ^a  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Genetic algorithms; Neural networks; Segmentation of MR and CT images

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTERIZED TOMOGRAPHY; FEATURE EXTRACTION; GENETIC ALGORITHMS; IMAGE SEGMENTATION; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING; WAVELET TRANSFORMS;

CANDIDATE NETWORK; HYPERPLANE; INTERSECTING PRISMS NEURAL NETWORK; RESTRICTED COULOMB ENERGY;

MULTILAYER NEURAL NETWORKS;

EID: 0036967684     PISSN: 13704621     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1021769530941     Document Type: Article

References (20)

1. Qian, W., Li, L. H. and Clarke, L. P.: Image feature extraction for mass detection in digital mammography-Influence of wavelet analysis, Medical Physics, 26(3) (1999). 402-408.
2. Tian, B., Shaikh, M. A., Azimisadjadi, M. R., Vonderhaar, T. H. and Reinke, D. L.: A study of cloud classification with neural networks using spectral and textural features. IEEE Trans. on Neural Networks, 10(1) (1999), 138-151.
3. Haering, N. and Lobo, N. D.: Features and classification methods to locate deciduous trees in images, Computer Vision and Image Understanding, 75(1-2) (1999), 133-149.
4. Ölmez, T. and Yazgan, E.: Abnormal tissue detection in computer tomography images using artificial neural networks, Proc. of the Annual Int. Conf. of the IEEE-EMBS, Paris, 1992, vol. 14, pp. 998-999.
5. Randen, T. and Husoy, J. H.: Filtering for texture classification- A comparative study, IEEE Trans. on Pattern Analysis and Machine Intelligence, 21(4) (1999), pp. 291-310.
6. Dokur, Z. and Ölmez, T.: Classification of magnetic resonance images using a novel neural network, IEEE-EMBS Asia Pacific Conference on Biomedical Engineering, 2000, Hangzhou China.
7. Reza, N. and Ying, S.: Classification of digital angiograms using artificial neural networks, 13th Ann. Int. Conf. of the IEEE-EMBS, 1991, vol. 13, no. 3, pp. 1440-1441.
8. Vinitski, S., Mohamed, F., Gonzalez, C., Knobler, R., Andrews, D., Iwanaga, T. and Madi, S.: Fast tissue segmentation based on a 3D and 4D feature map: Comparison study, 19th Annual Int. Conf. of the IEEE-EMBS, 1997, pp. 505-508.
9. Qian, L. S., Xiang, L., Cheng, L. K. and Liang, L. S.: Tissue classification of multi-spectral MR images of brain, 20th Annual Int. Conf. of the IEEE-EMBS, 1998, pp. 634-636.
10. Ozkan, M., Dawart, B. M. and Maciunas, R. J.: Neural network based segmentation of multi-modal medical images: A comparative and prospective study, IEEE Trans. on Medical Imaging, 12(3) (1993), 534-544.
11. Miller, A. S., Blott, B. H. and Hames, T. K.: Review of neural network applications in medical imaging and signal processing, Medical & Biological Engineering & Computing, 30 (1992), 449-464.
12. Reilly, D. L., Cooper, L. N. and Elboum, C.: A neural model for category learning, Biological Cybernetics, 45 (1982), 35-41.
13. Ölmez, T., Yazgan, E. and Ersoy, O. K.: Optimized competitive feature vector network, Electronics Letters, 30(24) (1994), 2052-2053.
14. Schaffer, J. D., Whitley, D. and Eshelman, L. J.: Combination of genetic algorithms and neural networks: A survey of the state of the art, Proc. Int. Wks on Combination of Genetic Algorithms and Neural Networks (COGANN-92), 1992, pp. 1-37.
15. Makhoul, J., Jaraudi, A. E. and Schwartz, R.: Formation of disconnected regions with a single hidden layer, IJCNN Int. Joint Conference on Neural Networks, vol. 1, 1989, pp. 455-460.
16. Dokur, Z., Ölmez, T. and Yazgan, E.: Comparison of discrete wavelet and Fourier transforms for ECG beat classification, Electronics, Letters, 35(18) (1999), 1502-1504.
17. Goldberg, D. E.: Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley Longman, Inc., Massachusetts, 1989.
18. Holland, J. H.: Genetic Algorithms, Scientific American, July (1992), 44-50.
19. Shareef, N., Wang, D. L.: and Yagel, R.: Segmentation of medical images using legion, IEEE Trans. on Medical Imaging, 18(1) (1999), 74-91.
20. Ölmez, T., and Dokur, Z.: ECG beat classification by a novel hybrid neural network and wavelet transform, IEEE-EMBS Asia Pacific Conference on Biomedical Engineering, 2000, Hangzhou China.