Visualization of boundaries in volumetric data sets through a what material you pick is what boundary you see approach. Issue 126 (April 2016)

• Record Type: Journal Article
• Authors: Li, Lu; Peng, Hu; Chen, Xun; Cheng, Juan; Gao, Dayong
• Is Part Of: Computer methods and programs in biomedicine. Issue 126(2016)
• Page Start: 76
• Page End: 88
• Publication Date: 2016-04
• Subjects: Direct volume rendering -- Transfer function -- Boundary visualization -- 3-D edge detection; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.11.014
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract : Highlights: Human-centric boundary extraction criteria and new boundary model. A novel boundary visualization method though a what material you pick is what boundary you see approach. Point-to-material distance measure. A complete application. Abstract: Transfer function design is a key issue in direct volume rendering. Many sophisticated transfer functions have been proposed to visualize boundaries in volumetric data sets such as computed tomography and magnetic resonance imaging. However, it is still conventionally challenging to reliably detect boundaries. Meanwhile, the interactive strategy is complicated for new users or even experts. In this paper, we first propose the human-centric boundary extraction criteria and our boundary model. Based on the model we present a boundary visualization method through a what material you pick is what boundary you see approach. Users can pick out the material of interest to directly convey semantics. In addition, the 3-D canny edge detection is utilized to ensure the good localization of boundaries. Furthermore, we establish a point-to-material distance measure to guarantee the accuracy and integrity of boundaries. The proposed boundary visualization is intuitive and flexible for the exploration of volumetric data.