Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30127
Hippocampus Segmentation using a Local Prior Model on its Boundary

Authors: Dimitrios Zarpalas, Anastasios Zafeiropoulos, Petros Daras, Nicos Maglaveras

Abstract:

Segmentation techniques based on Active Contour Models have been strongly benefited from the use of prior information during their evolution. Shape prior information is captured from a training set and is introduced in the optimization procedure to restrict the evolution into allowable shapes. In this way, the evolution converges onto regions even with weak boundaries. Although significant effort has been devoted on different ways of capturing and analyzing prior information, very little thought has been devoted on the way of combining image information with prior information. This paper focuses on a more natural way of incorporating the prior information in the level set framework. For proof of concept the method is applied on hippocampus segmentation in T1-MR images. Hippocampus segmentation is a very challenging task, due to the multivariate surrounding region and the missing boundary with the neighboring amygdala, whose intensities are identical. The proposed method, mimics the human segmentation way and thus shows enhancements in the segmentation accuracy.

Keywords: Medical imaging & processing, Brain MRI segmentation, hippocampus segmentation, hippocampus-amygdala missingboundary, weak boundary segmentation, region based segmentation, prior information, local weighting scheme in level sets, spatialdistribution of labels, gradient distribution on boundary.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330623

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385

References:


[1] X. Bresson, P. Vandergheynst and J.P. Thiran, "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, 2006.
[2] V. Caselles, R. Kimmel, G. Sapiro, "Geodesic active contours", International Journal of Computer Vision, 22(1), 61-79, 1997.
[3] T. Chan, W. Zhu, "Level set based shape prior segmentation", in Proc. IEEE Conf. Comp. Vision Pattern Recognition, 1164 - 1170, vol.2, 2005.
[4] T. Chan and L. Vese, "Active contours without edges", IEEE Trans. Image Processing, vol. 10, pp. 266277, 2001.
[5] J.G. Csernansky, L. Wang, D. Jones, D. Rastori-Cruz, J.A. Posener, G. Heydenbrand, J.P. Miller, M.I. Miller, "Hippocampal Deformities in Schizophrenia characterized by high dimensional brain mapping", American Journal of Psychiatry, 159:12, 2002.
[6] C. Davatzikos, X. Tao, and D. Shen, "Hierarchical active shape models, using the wavelet transform", IEEE Trans. on Medical Imaging, vol 22, no 3, 2003.
[7] J. M. Leventon, E. Grimson, and O. Faugeras, "Statistical shape influence in geodesic active contours", in Proc. IEEE Conf. Comp. Vision Pattern Recognition, vol. 1, pp. 316323, 2000.
[8] C. Li, C. Xu, C. Gui, and M. D. Fox, "Distance Regularized Level Set Evolution and its Application to Image Segmentation", IEEE Trans. Image Processing, vol. 19 (12), 2010.
[9] S. Loncaric, "A survey of shape analysis techniques", Pattern Recognition, vol.31, no 8, pp.938-1001, 1998.
[10] D.S. Marcus, T.H. Wang, J. Parker, J.G. Csernansky, J.C. Morris, and R.L. Buckner, "Open Access Series of Imaging Studies (OASIS): Cross-Sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults", Journal of Cognitive Neuroscience, 19, 1498- 1507.
[11] D. Martin, C. Fowlkes, and J. Malik, "Learning to detect natural image boundaries using local brightness, color and texture cues",IEEE Trans. on Pattern Analysis and Machine Intelligence, vol26, no 5, pp.530-549, 2004.
[12] D. Mumford, J. Shah, "Optimal approximation by piecewise smooth function and associated variational problems", Communication on Pure and Applied Mathematics 42, pp. 577685,1989.
[13] M.E. Shenton, G. Gerig, R.W. McCarley, G. Szekely, and R. Kikinis, "Amygdala-hippocampal shape differences in schizophrenia: the application of 3D shape models to volumetric MR data", Psychiatry Research Neuroimaging, 115, 15-35, 2002.
[14] J. Talairach, P Tournoux, "Co-planar strereotaxic atlas of the human brain: An approach to medical cerebral imaging", New York: Thieme, 1988.
[15] B. Vemuri and Y. Chen, "Joint image registration and segmentation", Geometric level set methods in Imaging, Vision and Graphics, Springer, pp. 251-269, 2003.
[16] J. Yang, L.H. Staib and J.S. Duncan, "Neighbor-Constrained Segmentation with Level Set Based 3D Deformable Models", IEEE Trans. on Medical Imaging, vol. 23(8), 2004.
[17] K. Zhang, L. Zhang, H. Song, and W. Zhou, "Active contours with selective local or global segmentation: A new formulation and level set method", Image Vision Computing, 28(4): 668-676, 2010.
[18] Y. Zhang, B.J. Matuszewski, L.K. Shark, C.J. Moore, "Medical image segmentation using new hybrid level set method", IEEE Int. Conf. on Biomedical Visualization, 2008.