Graph based lumen segmentation in optical coherence tomography images

Mengdi Xu, Jun Cheng, Damon Wing Kee Wong, Jiang Liu, Akira Taruya, Atsushi Tanaka

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Intravascular optical coherence tomography (IVOCT) is a new invasive imaging system which produces high-resolution images of coronary arteries. Lumen segmentation plays an important role in subsequent analysis of IVOCT images. In this work, we develop a fully automatic lumen segmentation method on IVOCT images. A graph based method is applied to segment the vessel lumen and a match filter based method is employed to detect the guide-wire artifact which caused by guide-wire. A dataset of 500 IVOCT images with manually labeled lumen boundaries is used to evaluate the proposed approach. Overlap dice (OD) is computed to quantitatively evaluate the segmentation result. Results show that the proposed graph based segmentation method is accurate and efficient.

Original languageEnglish
Title of host publication2015 10th International Conference on Information, Communications and Signal Processing, ICICS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467372183
DOIs
Publication statusPublished - 26 Apr 2016
Externally publishedYes
Event10th International Conference on Information, Communications and Signal Processing, ICICS 2015 - Singapore, Singapore
Duration: 2 Dec 20154 Dec 2015

Publication series

Name2015 10th International Conference on Information, Communications and Signal Processing, ICICS 2015

Conference

Conference10th International Conference on Information, Communications and Signal Processing, ICICS 2015
Country/TerritorySingapore
CitySingapore
Period2/12/154/12/15

Keywords

  • Graph based method
  • lumen segmentation
  • OCT

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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