Adaptive Mesh Expansion Model (AMEM) for liver segmentation from CT image
This study proposes a novel adaptive mesh expansion model (AMEM) for liver segmentation from computed tomography images. The virtual deformable simplex model (DSM) is introduced to represent the mesh, in which the motion of each vertex can be easily manipulated. The balloon, edge, and gradient force...
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Published in | PloS one Vol. 10; no. 3; p. e0118064 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
13.03.2015
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | This study proposes a novel adaptive mesh expansion model (AMEM) for liver segmentation from computed tomography images. The virtual deformable simplex model (DSM) is introduced to represent the mesh, in which the motion of each vertex can be easily manipulated. The balloon, edge, and gradient forces are combined with the binary image to construct the external force of the deformable model, which can rapidly drive the DSM to approach the target liver boundaries. Moreover, tangential and normal forces are combined with the gradient image to control the internal force, such that the DSM degree of smoothness can be precisely controlled. The triangular facet of the DSM is adaptively decomposed into smaller triangular components, which can significantly improve the segmentation accuracy of the irregularly sharp corners of the liver. The proposed method is evaluated on the basis of different criteria applied to 10 clinical data sets. Experiments demonstrate that the proposed AMEM algorithm is effective and robust and thus outperforms six other up-to-date algorithms. Moreover, AMEM can achieve a mean overlap error of 6.8% and a mean volume difference of 2.7%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 1.3 mm and 2.7 mm, respectively. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceived and designed the experiments: XW JY YW. Performed the experiments: XW JY ST. Analyzed the data: DA XW YZ ST. Contributed reagents/materials/analysis tools: YZ JY XW YW. Wrote the paper: XW JY DA. Competing Interests: The authors have declared that no competing interests exist. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0118064 |