Detection and Reconstruction of an Implicit Boundary Surface by Adaptively Expanding A Small Surface Patch in a 3D Image

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 metho...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 20(2014), 11 vom: 11. Nov., Seite 1490-506
1. Verfasser: Wang, Lisheng (VerfasserIn)
Weitere Verfasser: Wang, Pai, Cheng, Liuhang, Ma, Yu, Wu, Shenzhi, Wang, Yu-Ping, Xu, Zongben
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung: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
Beschreibung:Date Completed 07.03.2016
Date Revised 11.09.2015
published: Print
Citation Status MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2014.2312015