Abstract
A newly developed imaging technique called light-sheet laser microscopy imaging can visualize the detailed 3D structures of capillaries. Capillaries form complicated network structures in the obtained data, and this makes it difficult to model vessel structures by existing methods that implicitly assume simple tree structures for blood vessels. To cope with such dense capillaries with network structures, we propose to track the flow of blood vessels along a base-axis using a multiple-object tracking framework. We first track multiple blood vessels in cross-sectional images along a single axis to make the trajectories of blood vessels, and then connect these blood vessels to reveal their entire structures. This framework is efficient to track densely distributed vessels since it uses only a single cross-sectional plane. The network structure is then generated in the post-processing by connecting blood vessels on the basis of orientations of the trajectories. The results of experiments using a challenging real data-set demonstrate the efficacy of the proposed method, which are capable of modeling dense capillaries.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 |
| Publisher | IEEE Computer Society |
| Pages | 1333-1341 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781467388504 |
| DOIs | |
| Publication status | Published - Dec 16 2016 |
| Externally published | Yes |
| Event | 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 - Las Vegas, United States Duration: Jun 26 2016 → Jul 1 2016 |
Other
| Other | 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 |
|---|---|
| Country | United States |
| City | Las Vegas |
| Period | 6/26/16 → 7/1/16 |
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All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
Cite this
3D Structure Modeling of Dense Capillaries by Multi-objects Tracking. / Bise, Ryoma; Sato, Imari; Kajiya, Kentaro; Yamashita, Toyonobu.
Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. IEEE Computer Society, 2016. p. 1333-1341 7789658.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - 3D Structure Modeling of Dense Capillaries by Multi-objects Tracking
AU - Bise, Ryoma
AU - Sato, Imari
AU - Kajiya, Kentaro
AU - Yamashita, Toyonobu
PY - 2016/12/16
Y1 - 2016/12/16
N2 - A newly developed imaging technique called light-sheet laser microscopy imaging can visualize the detailed 3D structures of capillaries. Capillaries form complicated network structures in the obtained data, and this makes it difficult to model vessel structures by existing methods that implicitly assume simple tree structures for blood vessels. To cope with such dense capillaries with network structures, we propose to track the flow of blood vessels along a base-axis using a multiple-object tracking framework. We first track multiple blood vessels in cross-sectional images along a single axis to make the trajectories of blood vessels, and then connect these blood vessels to reveal their entire structures. This framework is efficient to track densely distributed vessels since it uses only a single cross-sectional plane. The network structure is then generated in the post-processing by connecting blood vessels on the basis of orientations of the trajectories. The results of experiments using a challenging real data-set demonstrate the efficacy of the proposed method, which are capable of modeling dense capillaries.
AB - A newly developed imaging technique called light-sheet laser microscopy imaging can visualize the detailed 3D structures of capillaries. Capillaries form complicated network structures in the obtained data, and this makes it difficult to model vessel structures by existing methods that implicitly assume simple tree structures for blood vessels. To cope with such dense capillaries with network structures, we propose to track the flow of blood vessels along a base-axis using a multiple-object tracking framework. We first track multiple blood vessels in cross-sectional images along a single axis to make the trajectories of blood vessels, and then connect these blood vessels to reveal their entire structures. This framework is efficient to track densely distributed vessels since it uses only a single cross-sectional plane. The network structure is then generated in the post-processing by connecting blood vessels on the basis of orientations of the trajectories. The results of experiments using a challenging real data-set demonstrate the efficacy of the proposed method, which are capable of modeling dense capillaries.
UR - http://www.scopus.com/inward/record.url?scp=85010190428&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85010190428&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2016.168
DO - 10.1109/CVPRW.2016.168
M3 - Conference contribution
AN - SCOPUS:85010190428
SP - 1333
EP - 1341
BT - Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
PB - IEEE Computer Society
ER -