Name
Abstract | ||
|---|---|---|
Volume rendering has long been used as a key technique for volume data visualization, which works by using a transfer function to map color and opacity to each voxel. Many volume rendering approaches proposed so far for voxels classification have been limited in a single global transfer function, which is in general unable to properly visualize interested structures. In this paper, we propose a localized volume data visualization approach which regards volume visualization as a combination of two mutually related processes: the segmentation of interested structures and the visualization using a locally designed transfer function for each individual structure of interest. As shown in our work, a new interactive segmentation algorithm is advanced via skeletons to properly categorize interested structures. In addition, a localized transfer function is subsequently presented to assign optical parameters via interested information such as intensity, thickness and distance. As can be seen from the experimental results, the proposed techniques allow to appropriately visualize interested structures in highly complex volume medical data sets. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TVCG.2010.239 | IEEE Trans. Vis. Comput. Graph. |
Keywords | Field | DocType |
skeleton cuts,interested structure,interested information,localized transfer function,color mapping,volume rendering,image segmentation,segmentation,efficient segmentation method,categorize interested structure,complex volume,bone,rendering (computer graphics),localized volume data,image classification,data visualisation,volume visualization,classification,complex medical sets,transfer function,voxel classification,interactive systems,visual parameters,volume data visualization,interactive segmentation algorithm,medical image processing,opacity mapping,image colour analysis,three dimensional,indexing terms,euclidean distance,skeleton,computer graphic,visualization,transfer functions,data visualization | Voxel,Computer vision,Volume rendering,Data visualization,Segmentation,Computer science,Visualization,Image segmentation,Artificial intelligence,Contextual image classification,Computer graphics | Journal |
Volume | Issue | ISSN |
17 | 9 | 1941-0506 |
Citations | PageRank | References |
13 | 0.65 | 31 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dehui Xiang | 1 | 92 | 13.67 |
| Jie Tian | 2 | 1475 | 159.24 |
| Fei Yang | 3 | 13 | 0.65 |
| Qi Yang | 4 | 32 | 4.73 |
| Xing Zhang | 5 | 155 | 32.89 |
| Qingde Li | 6 | 59 | 8.67 |
| Xin Liu | 7 | 25 | 6.64 |