Volumetric Data Exploration is a computational methodology within the field of scientific visualization that enables the interactive analysis and interpretation of three-dimensional scalar fields by directly probing, navigating, and extracting meaningful structural and contextual information from volumetric datasets.
223
Publications
42.8K
Citations
778
Authors
288
Institutions
Publications per year
2017–2026
30
Parents
Publications
223
1–5 of 223
Authors
778
- KM
10
h-index
- DS
10
h-index
- ME
9
h-index
- CH
9
h-index
- TE
7
h-index
1–5 of 778
Institutions
288
University of Utah
Salt Lake City, United States
15 h-index
39 publications
2K citations
TU Wien
Vienna, Austria
11 h-index
22 publications
1.3K citations
Purdue University West Lafayette
West Lafayette, United States
10 h-index
23 publications
1.2K citations
The Ohio State University
Columbus, United States
10 h-index
16 publications
707 citations
University of California, Davis
Davis, United States
10 h-index
20 publications
1.4K citations
VRVis GmbH (Austria)
Vienna, Austria
6 h-index
12 publications
755 citations
The University of Texas at Austin
Austin, United States
6 h-index
10 publications
422 citations
University of California San Diego
San Diego, United States
6 h-index
9 publications
333 citations
1–8 of 288
Venues
- IEEE Transactions on Visualization and Computer Graphics
TVCG · 40 publications · 2.2K citations
28
h-index
- Computer Graphics Forum
12 publications · 494 citations
11
h-index
- The Visual Computer
7 publications · 154 citations
7
h-index
- IEEE Computer Graphics and Applications
5 publications · 202 citations
5
h-index
- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
5 publications · 594 citations
5
h-index
1–5