3D Active Vessel Tracking Using an Elliptical Prior

Jiwoo Kang, Suwoong Heo, WooJin Hyung, Joon Seok Lim, Sanghoon Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, we propose a novel vessel tracking method, called active vessel tracking (AVT). The proposed method retains the major advantages that most 2D segmentation methods have demonstrated for 3D tracking while overcoming the drawbacks of previous 3D vessel tracking methods. Under the assumption that the vessel is cylindrical, thereby making its cross-section elliptical, the AVT finds a plane perpendicular to the vessel axis while tracking the vessel along its length. Also, We propose a method for vessel branch detection to automatically track complete vascular networks from a single starting point, whereas the previously proposed solutions have usually been limited in handling vessel bifurcations precisely on 3D or have required considerable user interaction. Our results show that the method is robust and accurate in both synthetic and clinical cases. In an experiment on synthetic data sets, the proposed method achieved a tracking accuracy of 96.1±0.5, detecting 99.1% of the branches. In an experiment on abdominal CTA data sets, it achieved a tracking accuracy of 98.4±0.5 for six target vessels, detecting 98.3% of the branches. These results show that the proposed method can outperform previous methods for vessel tracking.

Original languageEnglish
Article number8424240
Pages (from-to)5933-5946
Number of pages14
JournalIEEE Transactions on Image Processing
Volume27
Issue number12
DOIs
Publication statusPublished - 2018 Dec 1

Fingerprint

Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

Cite this

Kang, Jiwoo ; Heo, Suwoong ; Hyung, WooJin ; Lim, Joon Seok ; Lee, Sanghoon. / 3D Active Vessel Tracking Using an Elliptical Prior. In: IEEE Transactions on Image Processing. 2018 ; Vol. 27, No. 12. pp. 5933-5946.
@article{c41ed78810444a47a0316c230cbdffe5,
title = "3D Active Vessel Tracking Using an Elliptical Prior",
abstract = "In this paper, we propose a novel vessel tracking method, called active vessel tracking (AVT). The proposed method retains the major advantages that most 2D segmentation methods have demonstrated for 3D tracking while overcoming the drawbacks of previous 3D vessel tracking methods. Under the assumption that the vessel is cylindrical, thereby making its cross-section elliptical, the AVT finds a plane perpendicular to the vessel axis while tracking the vessel along its length. Also, We propose a method for vessel branch detection to automatically track complete vascular networks from a single starting point, whereas the previously proposed solutions have usually been limited in handling vessel bifurcations precisely on 3D or have required considerable user interaction. Our results show that the method is robust and accurate in both synthetic and clinical cases. In an experiment on synthetic data sets, the proposed method achieved a tracking accuracy of 96.1±0.5, detecting 99.1{\%} of the branches. In an experiment on abdominal CTA data sets, it achieved a tracking accuracy of 98.4±0.5 for six target vessels, detecting 98.3{\%} of the branches. These results show that the proposed method can outperform previous methods for vessel tracking.",
author = "Jiwoo Kang and Suwoong Heo and WooJin Hyung and Lim, {Joon Seok} and Sanghoon Lee",
year = "2018",
month = "12",
day = "1",
doi = "10.1109/TIP.2018.2862346",
language = "English",
volume = "27",
pages = "5933--5946",
journal = "IEEE Transactions on Image Processing",
issn = "1057-7149",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "12",

}

3D Active Vessel Tracking Using an Elliptical Prior. / Kang, Jiwoo; Heo, Suwoong; Hyung, WooJin; Lim, Joon Seok; Lee, Sanghoon.

In: IEEE Transactions on Image Processing, Vol. 27, No. 12, 8424240, 01.12.2018, p. 5933-5946.

Research output: Contribution to journalArticle

TY - JOUR

T1 - 3D Active Vessel Tracking Using an Elliptical Prior

AU - Kang, Jiwoo

AU - Heo, Suwoong

AU - Hyung, WooJin

AU - Lim, Joon Seok

AU - Lee, Sanghoon

PY - 2018/12/1

Y1 - 2018/12/1

N2 - In this paper, we propose a novel vessel tracking method, called active vessel tracking (AVT). The proposed method retains the major advantages that most 2D segmentation methods have demonstrated for 3D tracking while overcoming the drawbacks of previous 3D vessel tracking methods. Under the assumption that the vessel is cylindrical, thereby making its cross-section elliptical, the AVT finds a plane perpendicular to the vessel axis while tracking the vessel along its length. Also, We propose a method for vessel branch detection to automatically track complete vascular networks from a single starting point, whereas the previously proposed solutions have usually been limited in handling vessel bifurcations precisely on 3D or have required considerable user interaction. Our results show that the method is robust and accurate in both synthetic and clinical cases. In an experiment on synthetic data sets, the proposed method achieved a tracking accuracy of 96.1±0.5, detecting 99.1% of the branches. In an experiment on abdominal CTA data sets, it achieved a tracking accuracy of 98.4±0.5 for six target vessels, detecting 98.3% of the branches. These results show that the proposed method can outperform previous methods for vessel tracking.

AB - In this paper, we propose a novel vessel tracking method, called active vessel tracking (AVT). The proposed method retains the major advantages that most 2D segmentation methods have demonstrated for 3D tracking while overcoming the drawbacks of previous 3D vessel tracking methods. Under the assumption that the vessel is cylindrical, thereby making its cross-section elliptical, the AVT finds a plane perpendicular to the vessel axis while tracking the vessel along its length. Also, We propose a method for vessel branch detection to automatically track complete vascular networks from a single starting point, whereas the previously proposed solutions have usually been limited in handling vessel bifurcations precisely on 3D or have required considerable user interaction. Our results show that the method is robust and accurate in both synthetic and clinical cases. In an experiment on synthetic data sets, the proposed method achieved a tracking accuracy of 96.1±0.5, detecting 99.1% of the branches. In an experiment on abdominal CTA data sets, it achieved a tracking accuracy of 98.4±0.5 for six target vessels, detecting 98.3% of the branches. These results show that the proposed method can outperform previous methods for vessel tracking.

UR - http://www.scopus.com/inward/record.url?scp=85050989463&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85050989463&partnerID=8YFLogxK

U2 - 10.1109/TIP.2018.2862346

DO - 10.1109/TIP.2018.2862346

M3 - Article

VL - 27

SP - 5933

EP - 5946

JO - IEEE Transactions on Image Processing

JF - IEEE Transactions on Image Processing

SN - 1057-7149

IS - 12

M1 - 8424240

ER -