Abstract
In this paper, a new technique (SPASM) based on a 3D-ASM is presented for automatic segmentation of cardiac MRI image data sets consisting of multiple planes with different orientations, and with large undersampled regions. SPASM was applied to sparsely sampled and radially oriented cardiac LV image data.
Performance of SPASM has been compared to results from other methods reported in literature. The accuracy of SPASM is comparable to these other methods, but SPASM uses considerably less image data.
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References
Bloomer, T.N., Plein, S., Radjenovic, A., Higgins, D.M., Jones, T.R., Ridgway, J.P., Sivananthan, M.U.: Cine mri using steady state free precession in the radial long axis orientation is a fast accurate method for obtaining volumetric data of the left ventricle. Journal of Magnetic Resonance Imaging 14, 685–692 (2001)
Cootes, T.F., Cooper, D., Taylor, C.J., Graham, J.: Active shape models - their training and application. Computer Vision and Image Understanding 61(1), 38–59 (1995)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Transactions on Patern Analysis and Machine Intelligence 23(6), 681–685 (2001)
van Assen, H.C., Danilouchkine, M.G., Dirksen, M.S., Reiber, J.H.C., Lelieveldt, B.P.F.: A 3d-active shape model driven by fuzzy inference: Application to cardiac ct and mr (submitted)
Kaus, M.R., von Berg, J., Weese, J., Niessen, W., Pekar, V.: Automated segmentation of the left ventricle in cardiac mri. Medical Image Analysis 8(13), 245–254 (2004)
Mitchell, S.C., Bosch, J.G., Lelieveldt, B.P.F., van der Geest, R.J., Reiber, J.H.C., Sonka, M.: 3d active appearance models: Segmentation of cardiac mr and ultrasound images. IEEE Transactions on Medical Imaging 21(9), 1167–1178 (2002)
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)
Rückert, D., Frangi, A.F., Schnabel, J.A.: Automatic construction of 3-d statistical deformation models of the brain using nonrigid registration. IEEE Transactions on Medical Imaging 22(8), 1014–1025 (2003)
Frangi, A.F., Rueckert, D., Schnabel, J.A., Niessen, W.J.: Automatic construction of multiple-object three-dimensional statistical shape models: Application to cardiac modeling. IEEE Transactions on Medical Imaging 21(9), 1151–1166 (2002)
Chandrashekara, R., Rao, A., Sanchez-Ortiz, G.I., Mohiaddin, R.H., Rückert, D.: Construction of a statistical model for cardiac motion analysis using nonrigid image registration. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 599–610. Springer, Heidelberg (2003)
Lötjönen, J., Kivistö, S., Koikkalainen, J., Smutek, D., Lauerma, K.: Statistical shape model of atria, ventricles and epicardium from short- and long-axis mr images. Medical Image Analysis 8, 371–386 (2004)
Yushkevic, P., Fletcher, P.T., Joshi, S., Thall, A., Pizer, S.M.: Continuous medial representations for geometric object modeling in 2d and 3d. Image and Vision Computing 21(1), 17–27 (2003)
Ordas, S., Boisrobert, L., Bossa, M., Laucelli, M., Huguet, M., Olmos, S., Frangi, A.: Grid-enabled automatic construction of a two-chamber cardiac PDM from a large database of dynamic 3D shapes. IEEE International Symposium of Biomedical Imaging, 416–419 (2004)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions of Systems, Man and Cybernetics 15(1), 116–132 (1985)
Cootes, T.F., Cooper, D., Taylor, C.J., Graham, J.: A trainable method of parametric shape description. Image and Vision Computing 10(5), 289–294 (1992)
Cootes, T.F., Taylor, C.J.: Statistical models of appearance for computer vision. Imaging Science and Biomedical Engineering, University of Manchester, Manchester M13 9PT, U.K., http://www.isbe.man.ac.uk/~bim/Models/app_models.pdf ; Tech. Rep. (March 2004)
Gower, J.: Generalized procrustes analysis. Psychometrika 40, 33–50 (1975)
Besl, P.J., McKay, N.D.: A method for registration of 3-d shapes. IEEE Transaction on Pattern Analysis and Machine Intelligence 14, 239–256 (1992)
Paulsen, R.R., Hilger, K.B.: Shape modeling using markov random field restoration of point correspondences. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 1–12. Springer, Heidelberg (2003)
Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum press, New York (1981)
Ordas, S., van Assen, H.C., Lelieveldt, B.P.F., Frangi, A.F.: Segmentation performance assessment of an autolandmarked statistical shape model (submitted)
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van Assen, H.C. et al. (2005). SPASM: Segmentation of Sparse and Arbitrarily Oriented Cardiac MRI Data Using a 3D-ASM. In: Frangi, A.F., Radeva, P.I., Santos, A., Hernandez, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2005. Lecture Notes in Computer Science, vol 3504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494621_4
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DOI: https://doi.org/10.1007/11494621_4
Publisher Name: Springer, Berlin, Heidelberg
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