Abstract
We have recently presented the dynamic deformable elastic template (DET) model for the retrieval of personalised anatomical and functional models of the heart from dynamic cardiac image sequences. The dynamic DET model is a finite element deformable model, for which the minimum of the energy must satisfy a simplified equation of Dynamics. It yielded fairly accurate results during our valuation process on a 45 patients cine MRI database. However, it experienced difficulties when dealing with very large thickening throughout the cardiac cycle, or on highly pathological cases. In this paper, we introduce prescribed displacements as low level constraints to locally drive the model. Non prescribed contour nodes are displaced according to a combination of forces extracted from prescribed points and image gradient. Prescribing a few points in a whole sequence allows us to retrieve much better segmentations on rather difficult cases.
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References
Montagnat, J., Delingette, H.: 4D deformable models with temporal constraints: application to 4D cardiac image segmentation. Medical Image Analysis 9(1), 87–100 (2005)
Sermesant, M., Delingette, H., Ayache, N.: An Electromechanical Model of the Heart for Image Analysis and Simulation. IEEE Transactions in Medical Imaging 25(5), 612–625 (2006)
Billet, F., Sermesant, M., Delingette, H., Ayache, N.: Cardiac Motion Recovery and Boundary Conditions Estimation by Coupling an Electromechanical Model and Cine-MRI Data. In: Ayache, N., Delingette, H., Sermesant, M. (eds.) FIMH 2009. LNCS, vol. 5528, pp. 376–385. Springer, Heidelberg (2009)
Lynch, M., Ghita, O., Whelan, P.F.: Segmentation of the Left Ventricle of the Heart in 3D+t MRI Data Using an Optimised Non-Rigid Temporal Model. IEEE Transactions in Medical Imaging 27(2), 195–203 (2008)
Schaerer, J., Casta, C., Clarysse, P., Rouchdy, Y., Pousin, J.: A Dynamic Elastic Model for Segmentation and Tracking of the Heart in MR Image Sequences. Medical Image Analysis (in press)
Oppenheim, A.V., Schafer, R.W., Buck, J.R.: Discrete-time signal processing, 2nd edn. Prentice-Hall, Inc., Upper Saddle River (1999)
Ciarlet, P.G., Lions, J.-L.: Handbook of Numerical Analysis. Finite difference methods, Solution of equations in ℤn, vol. 1. North-Holland, Amsterdam (1990)
Peckar, W., Schnorr, C., Rohr, K., Stiehl, H.S.: Parameter-Free Elastic Deformation Approach for 2D and 3D Registration Using Prescribed Displacements. Journal of Mathematical Imaging and Vision 10(2), 143–162 (1999)
Zienkiewicz, O.C., Taylor And, R.L., Zhu, J.Z.: The Finite Element Method: Its Basis and Fundamentals. Butterworth-Heinemann, Butterworths (2005)
Radau, P., Lu, Y., Connelly, K., Paul, G., Dick, A.J., Wright, G.A.: Evaluation Framework for Algorithms Segmenting Short Axis Cardiac MRI. The MIDAS Journal - Cardiac MR Left Ventricle Segmentation Challenge, http://hdl.handle.net/10380/3070
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Casta, C., Clarysse, P., Pousin, J., Schaerer, J., Croisille, P., Zhu, YM. (2010). Incorporating Low-Level Constraints for the Retrieval of Personalised Heart Models from Dynamic MRI. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. STACOM 2010. Lecture Notes in Computer Science, vol 6364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15835-3_18
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DOI: https://doi.org/10.1007/978-3-642-15835-3_18
Publisher Name: Springer, Berlin, Heidelberg
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