Abstract
Anatomical shapes present a unique problem in terms of accurate representation and medical image segmentation. Three-dimensional statistical shape models have been extensively researched as a means of autonomously segmenting and representing models. We present a segmentation method driven by a statistical shape model based on a priori shape information from manually segmented training image sets. Our model is comprised of a stack of two-dimensional Fourier descriptors computed from the perimeters of the segmented training image sets after a transformation into a canonical coordinate frame. We apply our shape model to the segmentation of CT and MRI images of the distal femur via an original iterative method based on active contours. The results from the application of our novel method demonstrate its ability to accurately capture anatomical shape variations and guide segmentation. Our quantitative results are unique in that most similar previous work presents only qualitative results.
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References
Cootes, T., Taylor, C.: Active shape models—Smart snakes. In: Proc. British Mach. Vision Conf., pp. 266–275 (1992)
Taylor, C., Cootes, T., Hill, A., Haslam, J.: Medical Image Segmentation Using Active Shape Models. In: Proc. Medical Imaging Workshop, Brusseles, Belgium, pp. 121–143 (1995)
Kaus, M., Pekar, V., Lorenz, C., Truyen, R., Lobregt, S., Weese, J.: Automated 3-D PDM Construction from Segmented Images Using Deformable Models. IEEE Transactions on Medical Imaging 22(8), 1005–1013 (2003)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. Int. J. Comput. Vis. 1, 321–331 (1987)
Staib, L., Duncan, J.: Boundary Finding with Parametrically Deformable Models. IEEE PAMI 14(11), 1061–1075 (1992)
Persoon, E., Fu, K.: Shape Discrimination Using Fourier Descriptors. IEEE Trans. on Sys.Man, and Cyber SMC 7(3), 629–639 (1977)
Zahn, C., Roskies, R.: Fourier Descriptors for Plane Closed Curves. IEEE Transactions on Computers 21(3), 269–281 (1972)
Hutton, T., Buxton, B., Hammond, P., Potts, H.: Estimating Average Growth trajectories in Shape-Space Using Kernel Smoothing. IEEE Transactions on Medical Imaging 22(6), 747–753 (2003)
Cootes, T., Edwards, G., Taylor, C.: Active appearance models. In: Burkhardt, H., Neumann, B. (eds.) Proc. Eur. Conf. Computer Vision, vol. 2, pp. 484–498 (1998)
Cootes, T., Hill, A., Taylor, C., Haslam, J.: The Use of Active Shape Models for Locating Structures in Medical Images. Image and Vision Computing 12(6), 355–365 (1994)
Xu, C., Prince, J.: Gradient vector flow: A new external force for snakes. In: IEEE Proc. Conf. on Computer Vision and Pattern Recognition, pp. 66–71 (1997)
Kelemen, A., Székely, G., Gerig, G.: Elastic Model-Based Segmentation of 3-D Neuroradiological Data Sets. IEEE Transactions on Medical Imaging 18(10), 828–839 (1999)
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© 2004 Springer-Verlag Berlin Heidelberg
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Berg, E., Mahfouz, M., Debrunner, C., Hoff, W. (2004). A 2D Fourier Approach to Deformable Model Segmentation of 3D Medical Images. In: Sonka, M., Kakadiaris, I.A., Kybic, J. (eds) Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis. MMBIA CVAMIA 2004 2004. Lecture Notes in Computer Science, vol 3117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27816-0_16
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DOI: https://doi.org/10.1007/978-3-540-27816-0_16
Publisher Name: Springer, Berlin, Heidelberg
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