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Detection and Reconstruction of An Implicit Boundary Surface by Adaptively Expanding A Small Surface Patch in A 3D Image
PrePrint
ISSN: 1077-2626
In this paper we propose a novel and easy to use 3D reconstruction method. With the method, users only need to specify a small boundary surface patch in a 2D section image, and then an entire continuous implicit boundary surface (CIBS) can be automatically reconstructed from a 3D image. In the method, a hierarchical tracing strategy is used to grow the known boundary surface patch gradually in the 3D image. An adaptive detection technique is applied to detect boundary surface patches from different local regions. The technique is based on both context dependence and adaptive contrast detection as in the human vision system. A recognition technique is used to distinguish true boundary surface patches from the false ones in different cubes. By integrating these different approaches, a high-resolution CIBS model can be automatically reconstructed by adaptively expanding the small boundary surface patch in the 3D image. The effectiveness of our method is demonstrated by its applications to a variety of real 3D images, where the CIBS with complex shapes/branches and with varying gray values/gradient magnitudes can be well reconstructed. Our method is easy to use, which provides a valuable tool for 3D image visualization and analysis as needed in many applications.
Citation:
Yu Ma, Liuhang Cheng, Shenzhi Wu, Pai Wang, Xu Zongben, Yu-Ping Wang, "Detection and Reconstruction of An Implicit Boundary Surface by Adaptively Expanding A Small Surface Patch in A 3D Image," IEEE Transactions on Visualization and Computer Graphics, 17 March 2014. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TVCG.2014.2312015>
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