Abstract
In neuroscience, grating cells in areas V1 and V2 of the visual cortex of monkeys can respond vigorously to a grating of bars of appropriate orientation, position and periodicity. Computational models of grating cells have been proposed and used to make texture analysis for medical images. To improve the matching precision, the computation models of grating cells were applied to the responses of simple cells and not for the pixel values of the input image. In this paper, the computational models of grating cells is modified to express uncertain information. Multi-valued logic is introduced into the computation of the responses of the grating subunit. Texture pattern is computed by means of the modified computational model of grating cells. Experiments show that the content-based medical image retrieval system using the modified computational model of grating cells has good performance.
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References
Müller, H., Michoux, N., Bandon, D., Geissbuhler, A.: A Review of Content-based Image Retrieval Systems in Medical Applications – Clinical Benefits and Future Directions. International Journal of Medical Informatics 73, 1–23 (2004)
Greenspan, H., Pinhas, A.T.: Medical Image Categorization and Retrieval for PACS Using the GMM-KL Framework. IEEE Transactions on Information Technology in BioMedicine 11, 190–202 (2007)
Hubel, D.H., Wiesel, T.N.: Sequence Regularity and Geometry of Orientation Columns in the Monkey Striate Cortex. Journal of Comparative Neurology 158, 267–293 (1974)
Petkov, N., Kruizinga, P.: Computational Models of Visual Neurons Specialized in the Detection of Periodic and Aperiodic Oriented Visual Stimuli: Bar and Grating Cells. Biological Cybernetics 76, 83–96 (1997)
Smutek, D., Shimizu, A., Kobatake, H., Nawano, S., Tesar, L.: Texture Analysis of Hepatocellular Carcinoma and Liver Cysts in CT Images. In: Hamza, M.H. (ed.) Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications, vol. 520, pp. 56–59. ACTA Press, CA (2006)
Xue, J.H., Aleksandra, P., Wilfried, P., Etienne, K., Van De Walle, R., Ignace, L.: An Integrated Method of Adaptive Enhancement for Unsupervised Segmentation of MRI Brain Images. Pattern Recognition Letters 24, 2549–2560 (2003)
Arivazhagan, S., Ganesan, L.: Texture Classification Using Wavelet Transform. Pattern Recognition Letters 24, 1513–1521 (2003)
Zhang, G., Ma, Z.M., Cai, Z.P.: Directed Filter for Dominant Direction Fuzzy Set in Content-based Image Retrieval. In: Proceedings of the 22nd ACM Symposium on Applied Computing (SAC 2007), pp. 76–77. ACM Press, Seoul, Korea (2007)
Movshon, J.A., Thompson, I.D., Tolhurst, D.J.: Spatial Summation in the Receptive Fields of Simple Cells in the Cat’s Striate Cortex. J. Physiol. 283, 53–77 (1978)
Movshon, J.A., Thompson, I.D., Tolhurst, D.J.: Receptive Field Organisation of Complete Cells in the Cat’s Striate Cortex. J. Physiol. 283, 79–99 (1978)
Jones, J.P., Palmer, L.A.: An Evaluation of the Two-dimensional Gabor Filter Model of Simple Receptive Fields in Cat Striate Cortex. J. Neurophysiology 58, 1233–1258 (1987)
Burr, D.C., Morrone, M.C., Spinelli, D.: Evidence for Edge and Bar Detectors in Human Vision. Vision Res. 29, 419–431 (1989)
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Zhang, G., Ma, Z.M., Cai, Z., Wang, H. (2008). Texture Analysis Using Modified Computational Model of Grating Cells in Content-Based Medical Image Retrieval. In: Gao, X., Müller, H., Loomes, M.J., Comley, R., Luo, S. (eds) Medical Imaging and Informatics. MIMI 2007. Lecture Notes in Computer Science, vol 4987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79490-5_17
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DOI: https://doi.org/10.1007/978-3-540-79490-5_17
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