3D Structure Modeling of Dense Capillaries by Multi-objects Tracking

Ryoma Bise, Imari Sato, Kentaro Kajiya, Toyonobu Yamashita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publicationProceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
PublisherIEEE Computer Society
Pages1333-1341
Number of pages9
ISBN (Electronic)9781467388504
DOIs
Publication statusPublished - Dec 16 2016
Externally publishedYes
Event29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 - Las Vegas, United States
Duration: Jun 26 2016Jul 1 2016

Other

Other29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
CountryUnited States
CityLas Vegas
Period6/26/167/1/16

Fingerprint

Blood vessels
Trajectories
Imaging techniques
Microscopic examination
Lasers
Processing
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Bise, R., Sato, I., Kajiya, K., & Yamashita, T. (2016). 3D Structure Modeling of Dense Capillaries by Multi-objects Tracking. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 (pp. 1333-1341). [7789658] IEEE Computer Society. https://doi.org/10.1109/CVPRW.2016.168

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 proceedingConference contribution

Bise, R, Sato, I, Kajiya, K & Yamashita, T 2016, 3D Structure Modeling of Dense Capillaries by Multi-objects Tracking. in Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016., 7789658, IEEE Computer Society, pp. 1333-1341, 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016, Las Vegas, United States, 6/26/16. https://doi.org/10.1109/CVPRW.2016.168
Bise R, Sato I, Kajiya K, Yamashita T. 3D Structure Modeling of Dense Capillaries by Multi-objects Tracking. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. IEEE Computer Society. 2016. p. 1333-1341. 7789658 https://doi.org/10.1109/CVPRW.2016.168
Bise, Ryoma ; Sato, Imari ; Kajiya, Kentaro ; Yamashita, Toyonobu. / 3D Structure Modeling of Dense Capillaries by Multi-objects Tracking. Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. IEEE Computer Society, 2016. pp. 1333-1341
@inproceedings{219439cdd04e4770b7921255b784f3da,
title = "3D Structure Modeling of Dense Capillaries by Multi-objects Tracking",
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.",
author = "Ryoma Bise and Imari Sato and Kentaro Kajiya and Toyonobu Yamashita",
year = "2016",
month = "12",
day = "16",
doi = "10.1109/CVPRW.2016.168",
language = "English",
pages = "1333--1341",
booktitle = "Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016",
publisher = "IEEE Computer Society",
address = "United States",

}

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 -