Graph Based Lumen Segmentation in Optical Coherence Tomography Images

Graph Based Lumen Segmentation in Optical Coherence Tomography Images
Title:
Graph Based Lumen Segmentation in Optical Coherence Tomography Images
Other Titles:
2015 10th International Conference on Information, Communications and Signal Processing (ICICS)
DOI:
10.1109/ICICS.2015.7459951
Keywords:
Publication Date:
02 December 2015
Citation:
M. Xu, J. Cheng, D. W. K. Wong, J. Liu, A. Taruya and A. Tanaka, "Graph based lumen segmentation in optical coherence tomography images," 2015 10th International Conference on Information, Communications and Signal Processing (ICICS), Singapore, 2015, pp. 1-5. doi: 10.1109/ICICS.2015.7459951
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.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISBN:
978-1-4673-7218-3
978-1-4673-7216-9
978-1-4673-7217-6
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