Abstract
This paper describes methods for the atlas-based segmentation of bone structures of the hip, the automatic detection of anatomical point landmarks and the computation of orthopedic parameters. An anatomical atlas was designed to replace interactive, time-consuming pre-processing steps needed for the virtual planning of hip operations. Furthermore, a non-linear gray value registration of CT data is used to recognize different bone structures of the hip. A surface based registration algorithm enables the robust and precise detection of anatomical point landmarks. Furthermore the determination of quantitative parameters, like angles, distances or sizes of contact areas, is important for the planning of hip operations. Based on segmented bone structures and detected landmarks algorithms for the automatic computation of orthopedic parameters were implemented. A first evaluation of the presented methods will be given at the end of the paper.
Chapter PDF
Similar content being viewed by others
References
DiGioia, A.M., et al.: Hipnav: pre-operative planning and intra-operative navigational guidance for acetabular implant placement in total hip replacement surgery. In: Proc. of Computer Assisted Orthopedic Surgery, Bern (1995)
Handels, H., Ehrhardt, J., Strathmann, B., Pl tz, W., P ppl, S.: Three-dimensional planning and simulation of hip operations and computer-assisted design of endoprostheses in bone tumor surgery. J. of Comp. Aided Surg. 6, 65–76 (2001)
Thirion, J.P.: Image matching as a diffusion process: an analogy with maxwell’s demons. Medical Image Analysis 2, 243–260 (1998)
Andresen, P.R., Nielsen, M.: Non-rigid registration by geometry–constrained diffusion. Medical Image Analysis 5, 81–88 (2001)
Schroeder, W.J., Martin, K., Lorensen, W.E.: The Visualization Toolkit, 2nd edn. Prentice-Hall, Englewood Cliffs (1998)
Smith, A.D.C.: The folding of the human brain: from shape to function. PhD thesis, University of London (1999)
Desbrun, M., Meyer, M., Schr der, P., Barr, A.: Implicit fairing of irregular meshes using diffusion curvature flow. In: SIGGRAPH 1999, pp. 317–324 (1999)
Ehrhardt, J., Handels, H., P ppl, S.J.: Atlas-based determination of anatomical landmarks to support the virtual planning of hip operations. In: CARS 2003, Elseviewer, Amsterdam (2003)
Clarenz, U., Dziuk, G., Rumpf, M.: On generalized mean curvature flow. In: Hildebrandt, S., Karcher, H. (eds.) Geometric Analysis and Nonlinear Partial Differential Equations, Springer, Heidelberg (2003)
Frantz, S., Rohr, K., Stiehl, H.S.: Improving the detection performance in semiautomatic landmark extraction. In: Taylor, C., Colchester, A. (eds.) MICCAI 1999. LNCS, vol. 1679, pp. 253–262. Springer, Heidelberg (1999)
Kass, M., Witkin, A.P., Terzopoulos, D.: Active contour models. In: IEEE Proc. of First Int. Conf. on Comp. Vision, London, pp. 259–269 (1987)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ehrhardt, J., Handels, H., Strathmann, B., Malina, T., Plötz, W., Pöppl, S.J. (2003). Atlas-Based Recognition of Anatomical Structures and Landmarks to Support the Virtual Three-Dimensional Planning of Hip Operations. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39899-8_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-39899-8_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20462-6
Online ISBN: 978-3-540-39899-8
eBook Packages: Springer Book Archive