Abstract
We present a new hierarchical graph representation for volume data as well as its associated operations to enable interactive feature segmentation for high-resolution volume data. Our method constructs a low-resolution graph which represents a coarser resolution of the data. This graph enables the user to interactively sample and edit a feature of interest by drawing strokes on data slices. A subgraph representing the feature is derived with a growing process, and is used to extract the high-resolution version of the feature from the original volume data by performing an automatic mapping and refinement procedure. Our three-level, graph-based approach overcomes partial volume effects that are introduced by downsampling the volume data, and enables interactive segmentation of fine features. We demonstrate the effectiveness of this approach with several challenging 3D segmentation applications.
| Original language | English (US) |
|---|---|
| Title of host publication | Advances in Visual Computing - First International Symposium, ISVC 2005, Proceedings |
| Pages | 143-150 |
| Number of pages | 8 |
| State | Published - Dec 1 2005 |
| Event | First International Symposium on Advances in Visual Computing, ISVC 2005 - Lake Tahoe, NV, United States Duration: Dec 5 2005 → Dec 7 2005 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3804 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | First International Symposium on Advances in Visual Computing, ISVC 2005 |
|---|---|
| Country | United States |
| City | Lake Tahoe, NV |
| Period | 12/5/05 → 12/7/05 |
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ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
A three-level graph based interactive volume segmentation system. / Huang, Runzhen; Ma, Kwan-Liu.
Advances in Visual Computing - First International Symposium, ISVC 2005, Proceedings. 2005. p. 143-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3804 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A three-level graph based interactive volume segmentation system
AU - Huang, Runzhen
AU - Ma, Kwan-Liu
PY - 2005/12/1
Y1 - 2005/12/1
N2 - We present a new hierarchical graph representation for volume data as well as its associated operations to enable interactive feature segmentation for high-resolution volume data. Our method constructs a low-resolution graph which represents a coarser resolution of the data. This graph enables the user to interactively sample and edit a feature of interest by drawing strokes on data slices. A subgraph representing the feature is derived with a growing process, and is used to extract the high-resolution version of the feature from the original volume data by performing an automatic mapping and refinement procedure. Our three-level, graph-based approach overcomes partial volume effects that are introduced by downsampling the volume data, and enables interactive segmentation of fine features. We demonstrate the effectiveness of this approach with several challenging 3D segmentation applications.
AB - We present a new hierarchical graph representation for volume data as well as its associated operations to enable interactive feature segmentation for high-resolution volume data. Our method constructs a low-resolution graph which represents a coarser resolution of the data. This graph enables the user to interactively sample and edit a feature of interest by drawing strokes on data slices. A subgraph representing the feature is derived with a growing process, and is used to extract the high-resolution version of the feature from the original volume data by performing an automatic mapping and refinement procedure. Our three-level, graph-based approach overcomes partial volume effects that are introduced by downsampling the volume data, and enables interactive segmentation of fine features. We demonstrate the effectiveness of this approach with several challenging 3D segmentation applications.
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UR - http://www.scopus.com/inward/citedby.url?scp=33744793768&partnerID=8YFLogxK
M3 - Conference contribution
SN - 3540307508
SN - 9783540307501
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 143
EP - 150
BT - Advances in Visual Computing - First International Symposium, ISVC 2005, Proceedings
ER -