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A Worm Model Based on Artificial Life for Automatic Segmentation of Medical Images

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Book cover Medical Imaging and Informatics (MIMI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4987))

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Abstract

An intelligent deformable model called worm model is constructed. The worm has a central nervous system, vision, perception and motor systems. It is able to memorize, recognize objects and control the motion of its body. The new model overcomes the defects of existing methods since it is able to process the segmentation of the image intelligently using more information available rather than using pixels and gradients only. The experimental results of segmentation of the corpus callosum from MRI brain images show that the proposed worm model is able to segment medical images automatically and accurately. For those images that are more complex or with fragmentary boundaries, the predominance of the worm model is especially clear.

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References

  1. Luo, S., Zhou, G.: Medical image processing and analysis, pp. 65–138. Science Press, Beijing (2003)

    Google Scholar 

  2. Montagnat, J., Delingette, H., Ayache, N.: A review of deformable surfaces: topology, geometry and deformation. Image and Vision Computing 19, 1023–1040 (2001)

    Article  Google Scholar 

  3. Pizer, S., Fletcher, P., Fridman, Y., Fritsch, D., Gash, A., Glotzer, J., Joshi, S., Thall, A., Tracton, G., Yushkevich, P., Chaney, E.: Deformable m-reps for 3D medical image segmentation. International Journal of Computer Vision 55, 85–106 (2003)

    Article  Google Scholar 

  4. Shen, D., Davatzikos, C.: An adaptive-focus deformable model using statistical and geometric information. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 906–913 (2000)

    Article  Google Scholar 

  5. Sebastian, T.B., Tek, H., Crisco, J.J., Kimia, B.B.: Segmentation of carpal bones from CT images using skeletally coupled deformable models. Medical Image Analysis 7, 21–45 (2003)

    Article  Google Scholar 

  6. Huang, W., Pan, Z.: Applications of Artificial Life in Computer Graphics. Journal of Computer-Aided Design & Computer Graphics 17, 1383–1388 (2005)

    Google Scholar 

  7. McInerney, T., Hamarneh, G., Sheton, M., Terzopoulos, D.: Deformable organisms for automatic medical image analysis. Medical Image Analysis 6, 251–266 (2002)

    Article  Google Scholar 

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Xiaohong Gao Henning Müller Martin J. Loomes Richard Comley Shuqian Luo

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© 2008 Springer-Verlag Berlin Heidelberg

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Feng, J., Wang, X., Luo, S. (2008). A Worm Model Based on Artificial Life for Automatic Segmentation of Medical Images. 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_6

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  • DOI: https://doi.org/10.1007/978-3-540-79490-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79489-9

  • Online ISBN: 978-3-540-79490-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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