Conference proceeding
A 3D Laplacian-Driven Parametric Deformable Model
2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), pp 279-286
01 Jan 2011
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
3D parametric deformable models have been used to extract volumetric object boundaries and they generate smooth boundary surfaces as results. However, in some segmentation cases, such as cerebral cortex with complex folds and creases, and human lung with high curvature boundary, parametric deformable models often suffer from over-smoothing or decreased mesh quality during model deformation. To address this problem, we propose a 3D Laplacian-driven parametric deformable model with a new internal force. Derived from a Mesh Laplacian, the internal force exerted on each control vertex can be decomposed into two orthogonal vectors based on the vertex's tangential plane. We then introduce a weighting function to control the contributions of the two vectors based on the model mesh's geometry. Deforming the new model is solving a linear system, so the new model can converge very efficiently. To validate the model's performance, we tested our method on various segmentation cases and compared our model with Finite Element and Level Set deformable models.
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Details
- Title
- A 3D Laplacian-Driven Parametric Deformable Model
- Creators
- Tian Shen - Lehigh UniversityXiaolei Huang - Lehigh UniversityHongsheng Li - Lehigh UniversityEdward Kim - Lehigh UniversityShaoting Zhang - Rutgers, The State University of New JerseyJunzhou Huang - The University of Texas at Arlington
- Publication Details
- 2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), pp 279-286
- Series
- IEEE International Conference on Computer Vision
- Publisher
- IEEE
- Number of pages
- 8
- Grant note
- IIS-0812120 / NSF; National Science Foundation (NSF) R21GM083928 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Web of Science ID
- WOS:000300061900036
- Scopus ID
- 2-s2.0-84863040815
- Other Identifier
- 991021884692504721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic