Song, S, Yang, J, Ai, D et al. (7 more authors) (2019) Patch-Based Adaptive Background Subtraction for Vascular Enhancement in X-Ray Cineangiograms. IEEE Journal of Biomedical and Health Informatics, 23 (6). pp. 2563-2575. ISSN 2168-2194
Abstract
OBJECTIVE:automatic vascular enhancement in X-ray cineangiography is of crucial interest, for instance, for better visualizing and quantifying coronary arteries in diagnostic and interventional procedures. METHODS:a novel patch-based adaptive background subtraction method (PABSM) is proposed automatically enhancing vessels in coronary X-ray cineangiography. First, pixels in the cineangiogram is described by the vesselness and Gabor features. Second, a classifier is utilized to separate the cineangiogram into the rough vascular and non-vascular region. Dilation is applied to the classified binary image to include more vascular region. Third, a patch-based background synthesis is utilized to fill the removed vascular region. RESULTS:a database containing 320 cineangiograms of 175 patients was collected, and then an interventional cardiologist annotated all vascular structures. The performance of PABSM is compared with six state-of-the-art vascular enhancement methods regarding the precision-recall curve and C-value. The area under the precision-recall curve is 0.7133, and the C-value is 0.9659. CONCLUSION:PABSM can automatically enhance the coronary artery in the cineangiograms. It preserves the integrity of vascular topological structures, particularly in complex vascular regions and removes noise caused by the non-uniform gray level distribution in the cineangiogram. SIGNIFICANCE:PABSM can reduce the motion artifacts and eases the subsequent vascular segmentation, which is crucial for the diagnosis and interventional procedures of coronary artery diseases.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. |
Keywords: | Learning, Adaptive Background, Enhancement, Coronary Cineangiography |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 777119 EPSRC EP/N026993/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jan 2019 11:47 |
Last Modified: | 19 Nov 2019 23:51 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Identification Number: | 10.1109/jbhi.2019.2892072 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141139 |