Machine Learning
An Intelligent System Approach to Higher-Dimensional Classification of Volume Data
IEEE Transactions on Visualization and Computer Graphics
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Fast Volume Segmentation With Simultaneous Visualization Using Programmable Graphics Hardware
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
GPU-based point radiation for interactive volume sculpting and segmentation
The Visual Computer: International Journal of Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Semi-supervised Tissue Segmentation of 3D Brain MR Images
IV '10 Proceedings of the 2010 14th International Conference Information Visualisation
A framework for volume segmentation and visualization using Augmented Reality
3DUI '10 Proceedings of the 2010 IEEE Symposium on 3D User Interfaces
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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.