Abstract
Extraction of bone contours from x-ray images is an important first step in computer analysis of medical images. It is more complex than the segmentation of CT and MR images because the regions delineated by bone contours are highly nonuniform in intensity and texture. Classical segmentation algorithms based on homogeneity criteria are not applicable. This paper presents a model-based approach for automatically extracting femur contours from hip x-ray images. The method works by first detecting prominent features, followed by registration of the model to the x-ray image according to these features. Then the model is refined using active contour algorithm to get the accurate result. Experiments show that this method can extract the contours of femurs with regular shapes, despite variations in size, shape and orientation.
This research is supported by NMRC/0482/2000.
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References
Chen, Y., Yap, W.H., Leow, W.K., Howe, T.S., Png, M.A.: Detecting femur fractures by texture analysis of trabeculae. In: Proc. ICPR 2004 (2004)
Lim, S.E., Xing, Y., Chen, Y., Leow, W.K., Howe, T.S., Png, M.A.: Detection of femur and radius fractures in x-ray images. In: Proc. 2nd Int. Conf. on Advances in Medical Signal and Information Processing (2004)
Lum, V.L.F., Leow, W.K., Chen, Y., Howe, T.S., Png, M.A.: Combining classifiers for bone fracture detection in x-ray images. In: Proc. ICIP (2005)
Lin, P., Zhang, F., Yang, Y., Zheng, C.: Carpal-bone feature extraction analysis in skeletal age assessment based on deformable model. J. of Computer Science and Technology (2004)
Rogowska, J.: Overview and fundamentals of medical image segmentation. In: Bankman, I.N. (ed.) Handbook of Medical Imaging, Processing and Analysis, pp. 69–85. Academic Press, London (2000)
Pham, D.L., Xu, C., Prince, J.L.: Current methods in medical image segmentation. Annual Review of Biomedical Engineering 2, 315–337 (2000)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. of Computer Vision 1, 321–331 (1987)
Cootes, T.F., Hill, A., Taylor, C.J., Haslam, J.: The use of active shape models for locating structures in medical images. Image and Vision Computing 12, 355–366 (1994)
Sethian, J.A.: Level Set Methods. Cambridge University Press, Cambridge (1996)
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)
Shen, D., Herskovits, E.H., Davatzikos, C.: An adaptive-focus statistical shape model for segmentation and shape modeling of 3-D brain structures. IEEE Trans. on Medical Imaging 20 (2001)
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)
Xu, C., Prince, J.L.: Gradient vector flow: A new external force for snakes. In: Proc. IEEE Conf. on CVPR 1997 (1997)
Foulonneau, A., Charbonnier, P., Heitz, F.: Geometric shape priors for region-based active contours. In: Proc. ICIP 2003 (2003)
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Chen, Y., Ee, X., Leow, W.K., Howe, T.S. (2005). Automatic Extraction of Femur Contours from Hip X-Ray Images. 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_21
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DOI: https://doi.org/10.1007/11569541_21
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