Abstract
We present a fully automated deformable model technique for myocardium segmentation in 3D MRI. Loss of signal due to blood flow, partial volume effects and significant variation of surface grey value appearance make this a difficult problem. We integrate various sources of prior knowledge learned from annotated image data into a deformable model. Inter-individual shape variation is represented by a statistical point distribution model, and the spatial relationship of the epi- and endocardium is modeled by adapting two coupled triangular surface meshes. To robustly accommodate variation of grey value appearance around the myocardiac surface, a prior parametric spatially varying feature model is established by classification of grey value surface profiles. Quantitative validation of 60 end-diastolic 3D MRI datasets demonstrates accuracy and robustness, with 1.28±0.81 mm mean deviation from manual segmentation. We investigate the extension to 4D by incorporating a constraint on the allowed deformation based on a learned example and show illustrative results for 4D MRI.
Chapter PDF
Similar content being viewed by others
References
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 484–498. Springer, Heidelberg (1998)
Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. Wiley and Sons, Chichester (1973)
Fletcher, P.T., Pizer, S.M., Gash, A.G., Joshi, S.: Deformable m-rep segmentation of object complexes. In: Proc. of ISBI, pp. 26–29. IEEE Press, Los Alamitos (2002)
Frangi, A., Niessen, W., Viergever, M.A.: Three-Dimensional Modeling for Functional Analysis of Cardiac Images: A Review. IEEE Trans. Med. Imag. 20(1), 2–25 (2001)
Jolly, M.-P., Duta, N., Funka-Lea, G.: Segmentation of the left ventricle in cardiac MR images. In: Proc. of ICCV, pp. 501–508. IEEE Computer Society, Los Alamitos (2001)
Kaus, M.R., Pekar, V., Lorenz, C., Truyen, R., Lobregt, S., Weese, J.: Automated 3D PDM construction from segmented images using deformable models. IEEE Trans. Med. Imag. 22(8), 1005–1013 (2003)
McInerney, T., Terzopoulos, D.: Deformable models in medical image analysis: A survey. Med. Img. Anal. 1(2), 91–108 (1996)
Mitchell, S.C., Lelieveldt, B.P.F., van der Geest, R.J., Bosch, H.G., Reiber, J.H.C., Sonka, M.: Multistage hybrid active appearance model matching: Segmentation of left and right ventricles in cardiac MR images. IEEE Trans. Med. Imag. 20(5), 415–423 (2001)
Lorenzo-Valdes, M., Sanchez-Ortiz, G.I., Mohiaddin, R.H., Rüeckert, D.: Atlas-based segmentation and tracking of 3D cardiac MR images using non-rigid registration. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2488, pp. 642–650. Springer, Heidelberg (2002)
Montagnat, J., Delingette, H.: Space and time shape constrained deformable surfaces for 4D medical image segmentation. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 196–205. Springer, Heidelberg (2000)
Weese, J., Kaus, M.R., Lorenz, C., Lobregt, S., Truyen, R., Pekar, V.: Shape constrained deformable models for 3D medical image segmentation. In: Insana, M.F., Leahy, R.M. (eds.) IPMI 2001. LNCS, vol. 2082, pp. 380–387. Springer, Heidelberg (2001)
Zeng, X., Staib, L.H., Schultz, R.T., Duncan, J.S.: Segmentation and measurement of the cortex from 3D MR images using coupled surfaces propagation. IEEE Trans. Med. Imag. 18(10), 927–937 (1999)
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
Kaus, M.R., von Berg, J., Niessen, W., Pekar, V. (2003). Automated Segmentation of the Left Ventricle in Cardiac MRI. 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_54
Download citation
DOI: https://doi.org/10.1007/978-3-540-39899-8_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20462-6
Online ISBN: 978-3-540-39899-8
eBook Packages: Springer Book Archive