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Volumetric segmentation of multiple basal ganglia structures using nonparametric coupled shape and inter-shape pose priors

Uzunbaş, Mustafa Gökhan and Soldea, Octavian and Çetin, Müjdat and Ünal, Gözde and Erçil, Aytül and Ünay, Devrim and Ekin, Ahmet and Fırat, Zeynep (2009) Volumetric segmentation of multiple basal ganglia structures using nonparametric coupled shape and inter-shape pose priors. In: IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2009), Boston, USA

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Abstract

We present a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. Neighboring anatomical structures in the human brain exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities based on training data, we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework, and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images and present a quantitative performance analysis. We compare our technique with existing methods and demonstrate the improvements it provides in terms of segmentation accuracy

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:MR imagery Volumetric segmentation active contours basal ganglia kernel density estimation moments shape prior
Subjects:Q Science > QA Mathematics > QA075 Electronic computers. Computer science
ID Code:13000
Deposited By:Gözde Ünal
Deposited On:02 Dec 2009 13:15
Last Modified:02 Dec 2009 14:20

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