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| Content Provider | ACM Digital Library |
|---|---|
| Author | Zhang, Xiangrong Zhao, Youbing Dong, Feng Clapworthy, Gordon J. Viceconti, Marco Chen, Wei |
| Abstract | Volume rendering is frequently used for visualising 3D volume data. In practical applications, there may be a need not only to render the volume data but also to directly select and edit it in a paradigm similar to image editing. Being the basis of volume editing, efficient volume selection tools can help users to locate and select the volume region of interest quickly and conveniently. However, semi-automatic volume selection has not been studied in depth in existing work. This short paper presents a status report of our current research on semi-automatic volume selection -- the intelligent volume brush iVolBrush -- as a segmentation tool for the EC-funded VPHOP project. The initial stage -- efficient 3D painting -- has been completed. Major improvements of VTK image selection, including the re-use of brush stencil data to avoid expensive stencil regeneration, have been made to enhance performance and meet the challenge of interactivity. Further intelligent selection features such as region-based or learning-based selection are being investigated and will be the focus of the next stage of the work. |
| Starting Page | 231 |
| Ending Page | 235 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781450304085 |
| DOI | 10.1145/1963564.1963604 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-12-27 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Volume brush Intelligent volume selection Region growing Semi-supervised classification 3d painting Vphop |
| Content Type | Text |
| Resource Type | Article |
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