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Computer Vision Techniques for Transcatheter Intervention

Feng Zhao, Mathew Roach, Xianghua Xie Orcid Logo, Matt Roach Orcid Logo

IEEE Journal of Translational Engineering in Health and Medicine

Swansea University Authors: Xianghua Xie Orcid Logo, Matt Roach Orcid Logo

DOI (Published version): 10.1109/JTEHM.2015.2446988

Abstract

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrilla...

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Published in: IEEE Journal of Translational Engineering in Health and Medicine
Published: 2015
Online Access: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7128336&queryText%3Dswansea+university
URI: https://cronfa.swan.ac.uk/Record/cronfa22239
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spelling 2019-05-30T16:46:12.7129588 v2 22239 2015-07-01 Computer Vision Techniques for Transcatheter Intervention b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 9722c301d5bbdc96e967cdc629290fec 0000-0002-1486-5537 Matt Roach Matt Roach true false 2015-07-01 SCS Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area. Journal Article IEEE Journal of Translational Engineering in Health and Medicine Medical image analysis, transcatheter Intervention, computer vision 18 6 2015 2015-06-18 10.1109/JTEHM.2015.2446988 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&amp;arnumber=7128336&amp;queryText%3Dswansea+university COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2019-05-30T16:46:12.7129588 2015-07-01T10:46:47.8243689 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Feng Zhao 1 Mathew Roach 2 Xianghua Xie 0000-0002-2701-8660 3 Matt Roach 0000-0002-1486-5537 4 0022239-01072015104926.pdf 07128336.pdf 2015-07-01T10:49:26.0730000 Output 9081839 application/pdf Version of Record true 2015-07-01T00:00:00.0000000 true
title Computer Vision Techniques for Transcatheter Intervention
spellingShingle Computer Vision Techniques for Transcatheter Intervention
Xianghua Xie
Matt Roach
title_short Computer Vision Techniques for Transcatheter Intervention
title_full Computer Vision Techniques for Transcatheter Intervention
title_fullStr Computer Vision Techniques for Transcatheter Intervention
title_full_unstemmed Computer Vision Techniques for Transcatheter Intervention
title_sort Computer Vision Techniques for Transcatheter Intervention
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
9722c301d5bbdc96e967cdc629290fec
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
9722c301d5bbdc96e967cdc629290fec_***_Matt Roach
author Xianghua Xie
Matt Roach
author2 Feng Zhao
Mathew Roach
Xianghua Xie
Matt Roach
format Journal article
container_title IEEE Journal of Translational Engineering in Health and Medicine
publishDate 2015
institution Swansea University
doi_str_mv 10.1109/JTEHM.2015.2446988
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&amp;arnumber=7128336&amp;queryText%3Dswansea+university
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description Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area.
published_date 2015-06-18T03:26:29Z
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score 11.013148

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