UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL
Alireza Fallahi, Mohammad Pooyan, Hassan Hashemi, Hassan Khotanlou, Mohammad Ali Oghabian, Kavous Firuznia
2010
Abstract
Uterine fibroid the most common benign tumor of the female pelvic affected 20%- 50% of the women in the world. The efficacy of medical treatment is gauged by shrinkage of the size of these tumors after surgery. Complex fibroids anatomy, nonhomogeneity region and missing boundary in some cases are a challenging task in the segmentation. In this paper, we present a method to robustly segment these fibroids on MRI and measure the volume. Our method is based on combination of two step Chan-Vese level set method and geometric shape prior model. With calculating an initial region inside the fibroid using Chan-Vese level sets method, rough segmentation obtained followed by a prior shape model. We found the algorithm efficient and that it has some good results.
References
- Bresson, X., Vandercheynst, P., and Thiran, J.P., 2006, A Variational Model for Object Segmentation Using Boundary Information and Shape Prior Driven by the Mumford-Shah Functional. International Journal of Computer Vision, 68(2):145-162.
- Caselles, V., Kimmel, R., and Sapiro, G., 1997, Geodesic active contours, Int. J. Computer Vision, 22(1); 61- 79.
- Chan, T.F. and Vese, L.A. 2001. Active contours without edges. IEEE Transactions on Image Processing, 10(2):266-277.
- Charpiat, G., Faugeras, O., and Keriven, R. 2003. Shape metrics, warping and statistics. In IEEE International Conference on Image Processing, 627-630.
- Chen, S. Thiruvenkadam, H. D. Tagare, F. Huang, D. Wilson, and E. A. Geiser, 2001, On the incorporation of shape priors into geometric active contours, IEEE Workshop on Variational and Level Set Methods in Computer Vision, 145-152.
- Cootes, T, F,. Taylor, C, J,. Cooper, D, H and Graham, J, 1995, Active shape models - their training and application, Computer Vision Image Understand., 61 (1);38-59.
- Cura M, Cura A , Bugnone A,. 2006, Role of Magnetic Resonance Imaging in Patient Selection for Uterine Artery Embolization. Acta Radiol ; 1105-1114.
- Guyon J.P, Foskey M,Kim J, Firat Z, Davis Ylward B,. 2003, VETOT,Volume Estimation and Tracking Over Time:Framework and Validation. Proceedings in MICCAI; 142:149.
- Jianhua Y , Chen D, Wenzhu L , Premkumar A., 2006, Uterine fibroid segmentation and volume measurement on MRI. Progress in biomedical optics and imaging;(7)
- Leventon, M. E,. Grimson, . W, E, L. and Faugeras, 2000, Statistical shape influence in geodesic active contours, in Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR), ;316-323.
- Mumford, D. and Shah, J., 1989, Optimal approximations of iecewise smooth functions and associated variational problems. Communications on Pure and Applied Mathematics, 42:577-685.
- Osher, S. and Sethian, J.A. 1988. Fronts propagating with curvaturedependent speed: Algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, 79(1):2-49.
- Paragios, N., Rousson, M., and Ramesh, V. 2003. Nonrigid registr ation using distance functions . Journal of Computer Vision and Image Understanding, 89(2- 3):142-165.
- Staib,V and, Duncan, J,S, 1992, Boundary finding with parametrically deformable models, IEEE Trans. Pattern Anal. and Machine Intell., vol. 14, no. 11, pp. 1061-1075, 1992.
- VeKaut, M, B,. 1993, Changing trends in treatment of leiomyomata uteri. Curr Opin Obstet Gynecol 5:301.
Paper Citation
in Harvard Style
Fallahi A., Pooyan M., Hashemi H., Khotanlou H., Ali Oghabian M. and Firuznia K. (2010). UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL . In Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010) ISBN 978-989-674-027-6, pages 51-55. DOI: 10.5220/0002831100510055
in Bibtex Style
@conference{imagapp10,
author={Alireza Fallahi and Mohammad Pooyan and Hassan Hashemi and Hassan Khotanlou and Mohammad Ali Oghabian and Kavous Firuznia},
title={UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL},
booktitle={Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010)},
year={2010},
pages={51-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002831100510055},
isbn={978-989-674-027-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010)
TI - UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL
SN - 978-989-674-027-6
AU - Fallahi A.
AU - Pooyan M.
AU - Hashemi H.
AU - Khotanlou H.
AU - Ali Oghabian M.
AU - Firuznia K.
PY - 2010
SP - 51
EP - 55
DO - 10.5220/0002831100510055