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Segmentation of 3D CT Volume Images Using a Single 2D Atlas

  • Conference paper
Computer Vision for Biomedical Image Applications (CVBIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3765))

Abstract

Segmentation of medical images is an important first step in the analysis of medical images. A lot of research has been performed on the segmentation of complex CT/MR images using the atlas-based approach. Most existing methods use 3D atlases which are more complex and difficult to control than 2D atlases. They have been applied mostly for the segmentation of brain images. This paper presents a method that can segment multiple slices of an abdominal CT volume using a single 2D atlas. Segmentation of human body images is considerably more difficult and challenging than brain image segmentation. Test results show that our method can handle large variations in shape and intensity between the atlas and the target CT images.

This research is supported by NUS ARF R-252-000-210-112.

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References

  1. Thurfjell, L., Bohm, C., Greitz, T., Eriksson, L.: Transformations and algorithms in a computerized brain atlas. IEEE Tran. on Nuclear Science 40, 1187–1191 (1993)

    Article  Google Scholar 

  2. Dawant, B.M., Hartmann, S.L., Thirion, J.P., Maes, F., Vandermeulen, D., Demaerel, P.: Automatic 3-D segmentation of internal structures of head in MR images using a combination of similarity and free-form transformations: Part I, methodology and validation on normal subjects. IEEE Trans. on Medical Imaging 18, 909–916 (1999)

    Article  Google Scholar 

  3. Hartmann, S.L., Parks, M.H., Martin, P.R., Dawant, B.M.: Automatic 3-D segmentation of internal structures of head in MR images using a combination of similarity and free-form transformations: Part II, validation on severely atrophied brains. IEEE Trans. on Medical Imaging 18, 917–926 (1999)

    Article  Google Scholar 

  4. Rueckert, D., Sanchez-Ortiz, G.I., Lorenzo-Valdés, M., Chandrashekara, R., Mohiaddin, R.: Non-rigid registration of cardiac MR: Application to motion modelling and atlas-based segmentation. In: IEEE Int. Symp. on Biomedical Imaging (2002)

    Google Scholar 

  5. Park, H., Bland, P.H., Meyer, C.R.: Construction of an abdominal probabilistic atlas and its application in segmentation. IEEE Trans. on Medical Imaging 22, 483–492 (2003)

    Article  Google Scholar 

  6. Cuadra, M., Pollo, C., Bardera, A., Cuisenaire, O., Villemure, J.G., Thiran, J.P.: Atlas-based segmentation of pathological MR brain images using a model of lesion growth. IEEE Trans. on Medical Imaging 23, 1301–1314 (2004)

    Article  Google Scholar 

  7. Lorenzo-Valdés, M., Sanchez-Ortiz, G.I., Elkington, A.G., Mohiaddin, R.H., Rueckert, D.: Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. Medical Image Analysis 8, 255–265 (2004)

    Article  Google Scholar 

  8. Aboutanos, G.B., Nikanne, J., Watkins, N., Dawant, B.M.: Model creation and deformation for the automatic segmentation of the brain in MR images. IEEE Trans. on Biomedical Engineering 46, 1346–1356 (1999)

    Article  Google Scholar 

  9. Lancaster, J.L., Glass, T.G., Lankipalli, B.R., Downs, H., Mayberg, H., Fox, P.T.: A modality-independent approach to spatial normalization. Human Brain Mapping 3, 209–223 (1995)

    Article  Google Scholar 

  10. Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. on Pattern Analysis and Machine Intelligence 14, 239–256 (1992)

    Article  Google Scholar 

  11. Cuisenaire, O., Thiran, J., Macq, B., Michel, C., Volder, A.D., Marques, F.: Automatic registration of 3D MR images with a computerized brain atlas. SPIE Medical Imaging 1719, 438–449 (1996)

    Google Scholar 

  12. Aboutanos, G.B., Nikanne, J., Watkins, N., Dawant, B.M.: Model creation and deformation for the automatic segmentation of the brain in MR images. IEEE Trans. on Biomedical Engineering 46, 1346–1356 (1999)

    Article  Google Scholar 

  13. Fleckenstein, P., Jensen, J.T.: Anatomy in Diagnostic Imaging. Munksgaard (1993)

    Google Scholar 

  14. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. of Computer Vision 1, 321–331 (1987)

    Article  Google Scholar 

  15. Xu, C., Prince, J.L.: Gradient vector flow: A new external force for snakes. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (1997)

    Google Scholar 

  16. Zijdenbos, A.P., Dawant, B.M., Margolin, R.A., Palmer, A.C.: Morphometric analysis of white matter lesions in MR images: Method and validation. IEEE Trans. on Medical Imaging 13, 716–724 (1994)

    Article  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Ding, F., Leow, W.K., Wang, SC. (2005). Segmentation of 3D CT Volume Images Using a Single 2D Atlas. In: Liu, Y., Jiang, T., Zhang, C. (eds) Computer Vision for Biomedical Image Applications. CVBIA 2005. Lecture Notes in Computer Science, vol 3765. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569541_46

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  • DOI: https://doi.org/10.1007/11569541_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29411-5

  • Online ISBN: 978-3-540-32125-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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