Abstract
This paper presents a novel segmentation approach featuring shape constraints of multiple structures. A framework is developed combining statistical shape modeling with a maximum a posteriori segmentation problem. The shape is characterized by signed distance maps and its modes of variations are generated through principle component analysis. To solve the maximum a posteriori segmentation problem a robust Expectation Maximization implementation is used. The Expectation Maximization segmenter generates a label map, calculates image intensity inhomogeneities, and considers shape constraints for each structure of interest. Our approach enables high quality segmentations of structures with weak image boundaries which is demonstrated by automatically segmenting 32 brain MRIs into right and left thalami.
Chapter PDF
Similar content being viewed by others
Keywords
- Principle Component Analysis
- Active Shape Model
- Intensity Inhomogeneity
- Statistical Shape Modeling
- Shape Constraint
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Leventon, M.E., Grimson, W.E.L., Faugeras, O.D.: Statistical shape influence in geodesic active contours. In: CVPR, pp. 1316–1323 (2000)
Tsai, A.Y., Wells III, W., Tempany, C., Fan, D.T.A., Grimson, W., Willsky, A.: A shape-based approach to the segmentation of medical imagery using level sets. IEEE Transaction on Medical Imaging 22(2), 137–154 (2003)
Rousson, R. D. M., Paragios, N.: Active shape models from a level set perspective Tech. Rep. 4984, Institut National de Recherche en Informatique eten Automatique, Sophia-Antipolis (2003), ftp://ftp.inria.fr/INRIA/publication/publi-pdf/RR/RR-4984.pdf
Cootes, T.F., Hill, A., Taylor, C.J., Haslam, J.: The use of active shape models for locating structures in medical imaging. Imaging and Vision Computing 12(6), 335–366 (1994)
Kelemen, A., Szekely, G., Gerig, G.: Elastic model-based segmentation of 3-d neuroradiological data sets medical imaging. IEEE Transactions on Medical Imaging 18, 828–839 (1999)
Pizer, S.M., Gerig, G., Joshi, S., Aylward, S.R.: Multiscale medial shape-based analysis of image objects. In: Proceedings of the IEEE, Special Issue on: Emerging Medical Imaging Technology, vol. 91, pp. 670–679 (2003)
Papdemetris, X., Sinusas, A.J., Dione, D.P., Todd Constable, R., Duncan, J.S.: Estimation of 3-d left ventricular deformation form medical images using biomechanical models. IEEE Transactions on Medical Imaging 21, 786–800 (2002)
Pohl, K.M., Bouix, S., Kikinis, R., Eric, W., Grimson, L.: Anatomical guided segmentation with non-stationary tissue class distributions in an expectation-maximization framework. In: ISBI, pp. 81–84 (2004)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance model. In: ECCV, vol. 2, pp. 484–498 (1998)
Warfield, S.K., Rexilius, J., Huppi, P.S., Inder, T.E., Miller, E.G., Wells, W.M., Zientara, G.P., Jolesz, F.A., Kikinis, R.: A binary entropy measure to assess nonrigid registration algorithm. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 266–274. Springer, Heidelberg (2001)
McLachlan, G.J., Krishnan, T.: The EM Algorithm and Extensions. John Wiley and Sons, Inc. Chichester (1997)
Wells III, W.M., Grimson, W.E.L., Kikinis, R., Jolesz, F.A.: Adaptive segmentation of MRI data. IEEE Transactions on Medical Imaging 15, 429–442 (1996)
Dice, L.R.: Measure of the amount of ecological association between species. Ecology 26, 297–302 (1945)
Pohl, K.M., Wells, W.M., Guimond, A., Kasai, K., Shenton, M.E., Kikinis, R., Grimson, W.E.L., Warfield, S.K.: Incorporating non-rigid registration into expectation maximization algorithm to segment MR images. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2488, pp. 564–572. Springer, Heidelberg (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pohl, K.M., Warfield, S.K., Kikinis, R., Grimson, W.E.L., Wells, W.M. (2004). Coupling Statistical Segmentation and PCA Shape Modeling. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-30135-6_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22976-6
Online ISBN: 978-3-540-30135-6
eBook Packages: Springer Book Archive