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 language | English |
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Article number | 8424240 |
Pages (from-to) | 5933-5946 |
Number of pages | 14 |
Journal | IEEE Transactions on Image Processing |
Volume | 27 |
Issue number | 12 |
DOIs | |
Publication status | Published - 2018 Dec |
Bibliographical note
Funding Information:Manuscript received August 17, 2017; revised March 19, 2018 and May 3, 2018; accepted July 12, 2018. Date of publication August 1, 2018; date of current version September 4, 2018. This work was supported by the National Research Foundation of Korea (NRF) through the Korea Government (MSIT) under Grant 2016R1A2B2014525. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Oleg V. Michailovich. (Corresponding author: Sanghoon Lee.) J. Kang, S. Heo, and S. Lee are with the Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail: jwkang@yonsei.ac.kr; heartshape@yonsei.ac.kr; slee@yonsei.ac.kr).
Publisher Copyright:
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All Science Journal Classification (ASJC) codes
- Software
- Computer Graphics and Computer-Aided Design