期刊论文详细信息
PATTERN RECOGNITION 卷:43
Topological active volumes: A topology-adaptive deformable model for volume segmentation
Article
Barreira, N.1  Penedo, M. G.1  Cohen, L.2  Ortega, M.1 
[1] Univ A Coruna, Dept Comp Sci, La Coruna, Spain
[2] Univ Paris 09, CEREMADE, CNRS, Appl Math & Image Anal Grp, F-75775 Paris 16, France
关键词: 3D image segmentation;    Topological active volumes;    Adaptive topology;   
DOI  :  10.1016/j.patcog.2009.06.005
来源: Elsevier
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【 摘 要 】

This paper proposes a generic methodology for segmentation and reconstruction of volumetric datasets based on a deformable model, the topological active volumes (TAV). This model, based on a polyhedral mesh, integrates features of region-based and boundary-based segmentation methods in order to fit the contours of the objects and model its inner topology. Moreover, it implements automatic procedures, the so-called topological changes, that alter the mesh structure and allow the segmentation of complex features such as pronounced curvatures or holes, as well as the detection of several objects in the scene. This work presents the TAV model and the segmentation methodology and explains how the changes in the TAV structure can improve the adjustment process. In particular, it is focused on the increase of the mesh density in complex image areas in order to improve the adjustment to object surfaces. The Suitability of the mesh structure and the segmentation methodology is analyzed and the accuracy of the proposed model is proved with both synthetic and real images. (C) 2009 Elsevier Ltd. All rights reserved.

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