Coupled nonparametric shape and moment-based intershape pose priors for multiple basal ganglia structure segmentation

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Uzunbaş, Mustafa Gökhan and Soldea, Octavian and Ünay, Devrim and Çetin, Müjdat and Ünal, Gözde and Erçil, Aytül and Ekin, Ahmet (2010) Coupled nonparametric shape and moment-based intershape pose priors for multiple basal ganglia structure segmentation. IEEE Transactions on Medical Imaging, 29 (12). pp. 1959-1978. ISSN 0278-0062

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Abstract

This paper presents a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. In biological tissues, such as the human brain, neighboring structures 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 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. We present a set of 2D and 3D experiments as well as a quantitative performance analysis. In addition, we perform a comparison to several existent segmentation methods and demonstrate the improvements provided by our approach in terms of segmentation accuracy.
Item Type: Article
Uncontrolled Keywords: Volumetric segmentation, active contours, shape prior, kernel density estimation, moments, MR imagery, basal ganglia
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 10 Dec 2010 16:08
Last Modified: 26 Apr 2022 08:44
URI: https://research.sabanciuniv.edu/id/eprint/16100

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