Abstract
Levelset methods were introduced in medical images segmentation by Malladi et al. in 1995. In this paper, we propose several improvements of the original method to speed up the algorithm convergence and to improve the quality of the segmentation in the case of cardiac gated SPECT images.
We studied several evolution criterions, taking into account the dynamic property of heart image sequences. For each step of the segmentation algorithm, we have compared different solutions in order to both reduce time and improve quality.
We have developed a modular segmentation tool with 3D+T visualization capabilities to experiment the proposed solutions and tune the algorithm parameters. We show segmentation results on both simulated and real SPECT images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
V. Caselles, F. Catte, T. Coll, and F. Dibos. A geometric model for active contours in image processing. In Numerische Mathematik, volume 66, pages 1–33, 1993.
V. Caselles, R. Kimmel, and G. Sapiro. Geodesic active contours. International Journal of Computer Vision, 22(1):61–79, 1997.
L.D. Cohen and Isaac Cohen. Finite element methods for active contour models and balloons for 2-D and 3-D images. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, 15, November 1993.
L.D. Cohen and Ron Kimmel. Global minimum for active contour models: A minimal path approach. Int. J. of Computer Vision, 24(1):57–78, 1997.
E. Debreuve, M. Barlaud, G. Aubert, I. Laurette, and J. Darcourt. Space time segmentation using level set active contours applied to myocardial gated spect. In International Conference on Medical Imaging (MIC99), Vancouver, Octobre 1999.
J. Gomes and O.D. Faugeras. Reconciling Distance Functions and Level Sets. Journal of Visual Communication and Image Representation, 11:209–223, 2000.
S. Jehan-Besson, M. Barlaud, and G. Aubert. A 3-step algorithm using region-based active contours for video objects detection. EURASIP Journal of Applied Signal Processing, 2002(6):572–581, 2002.
M. Kass, A. Witkin, and D. Terzopoulos. SNAKES: Active contour models. International Journal of Computer Vision, 1:321–332, January 1988.
R. Malladi, J. A. Sethian, and B.C. Vemuri. Shape modeling with front propagation: A level set approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(2):158–175, February 1995.
J. Montagnat and H. Delingette. A review of deformable surfaces: topology, geometry and deformation. Image and Vision Comput., 19(14):1023–1040, Dec. 2001.
S. Osher and J. Sethian. Fronts propagating with curvature dependent speed: algorithms based on the Hamilton-Jacobi formulation. Journal of Computational Physics, 79:12–49, 1988.
Nikos Paragios and Rachid Deriche. Geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(3):266–280, March 2000.
P.H. Pretorius, W. Xia, M. A. King, B. M. W. Tsui, T.-S. Pan, and B.J. Villegas. Determination of left and right ventricular volume and ejection fraction using a mathematical cardiac torso phantom for gated blood pool spect. Journal of Nuclear Medicine, 37:97, 1996.
M. Sussman, P. Smereka, and S. Osher. A level set approach for computing solutions to incompressible two-phase flow. J. Comput. Physics, 114:146–159, 1994.
D. Terzopoulos, A. Witkin, and M. Kass. Constraints on deformable models: Recovering 3d shape and non rigid motion. Artificial Intelligence, 36(1):91–123, 1988.
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
Charnoz, A., Lingrand, D., Montagnat, J. (2003). A Levelset Based Method for Segmenting the Heart in 3D+T Gated SPECT Images. In: Magnin, I.E., Montagnat, J., Clarysse, P., Nenonen, J., Katila, T. (eds) Functional Imaging and Modeling of the Heart. FIMH 2003. Lecture Notes in Computer Science, vol 2674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44883-7_6
Download citation
DOI: https://doi.org/10.1007/3-540-44883-7_6
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40262-6
Online ISBN: 978-3-540-44883-9
eBook Packages: Springer Book Archive