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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chartrand, G. Cresson, T. Chav, R. Gotra, A. Tang, A. DeGuise, J. |
| Copyright Year | 2014 |
| Description | Author affiliation: Lab. de Rech. en Imagerie et Orthopedie, Montréal, QC, Canada (Chartrand, G.; Cresson, T.; Chav, R.; DeGuise, J.) || Centre de Rech. du Centre Hospitalier, Univ. de Montreal (CRCHUM), Montréal, QC, Canada (Gotra, A.; Tang, A.) |
| Abstract | Liver volumetry is considered to be an accurate indicator of hepatic function and a prognostic indicator in hepatic surgery planning. Despite many years of research, automated liver segmentation remains an open challenge and manual segmentation is still widely used clinically although it is time-consuming and tedious. In this paper we propose a novel semi-automated segmentation method based on deformable models independent of training data. First, an initial shape of the liver is generated by variational interpolation from a few user-generated contours. A template-matching method then identifies target points corresponding to the liver boundary. Using a Laplacian mesh optimization framework, the geometric model is iteratively deformed until it converges to the liver boundary. This liver segmentation method was tested against 20 publicly available datasets and is shown to be fast and robust to pathological cases with a mean volumetric overlap error of 6.8% and an average runtime under 6 minutes. |
| Starting Page | 641 |
| Ending Page | 644 |
| File Size | 1572252 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467319614 |
| DOI | 10.1109/ISBI.2014.6867952 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-04-29 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Liver Shape Image segmentation Laplace equations Three-dimensional displays Deformable models Pathology CT-scan Segmentation Laplacian Optimization Interactive |
| Content Type | Text |
| Resource Type | Article |
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