Abstract
Multimodal volume data commonly found in medical imaging applications present both opportunities and challenges to segmentation and visualization tasks. This paper presents a user directed volume segmentation system. Through a spreadsheets interface, the user can interactively examine and refine segmentation results obtained from automatic clustering. In addition, the user can isolate or highlight a feature of interest in a volume based on different modalities, and see the corresponding segmented results. Our system is easy to use since the preliminary segmentation results are organized and presented to the user in a relation-aware fashion based on the spatial relations between the segmented regions. We demonstrate this system using two multimodal datasets.
| Original language | English (US) |
|---|---|
| Title of host publication | Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings |
| Pages | 92-99 |
| Number of pages | 8 |
| DOIs | |
| State | Published - Oct 25 2010 |
| Event | 1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010 - Beijing, China Duration: Sep 20 2010 → Sep 20 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 6357 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 9/20/10 → 9/20/10 |
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Keywords
- Multimodal Volume Data
- Segmentation
- User Interface
- Visualization
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Relation-aware spreadsheets for multimodal volume segmentation and visualization. / Zheng, Lin; Wu, Yingcai; Ma, Kwan-Liu.
Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings. 2010. p. 92-99 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6357 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Relation-aware spreadsheets for multimodal volume segmentation and visualization
AU - Zheng, Lin
AU - Wu, Yingcai
AU - Ma, Kwan-Liu
PY - 2010/10/25
Y1 - 2010/10/25
N2 - Multimodal volume data commonly found in medical imaging applications present both opportunities and challenges to segmentation and visualization tasks. This paper presents a user directed volume segmentation system. Through a spreadsheets interface, the user can interactively examine and refine segmentation results obtained from automatic clustering. In addition, the user can isolate or highlight a feature of interest in a volume based on different modalities, and see the corresponding segmented results. Our system is easy to use since the preliminary segmentation results are organized and presented to the user in a relation-aware fashion based on the spatial relations between the segmented regions. We demonstrate this system using two multimodal datasets.
AB - Multimodal volume data commonly found in medical imaging applications present both opportunities and challenges to segmentation and visualization tasks. This paper presents a user directed volume segmentation system. Through a spreadsheets interface, the user can interactively examine and refine segmentation results obtained from automatic clustering. In addition, the user can isolate or highlight a feature of interest in a volume based on different modalities, and see the corresponding segmented results. Our system is easy to use since the preliminary segmentation results are organized and presented to the user in a relation-aware fashion based on the spatial relations between the segmented regions. We demonstrate this system using two multimodal datasets.
KW - Multimodal Volume Data
KW - Segmentation
KW - User Interface
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=77958031442&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77958031442&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15948-0_12
DO - 10.1007/978-3-642-15948-0_12
M3 - Conference contribution
SN - 3642159478
SN - 9783642159473
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 92
EP - 99
BT - Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings
ER -