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Neural Network Boundary Detection for 3D Vessel Segmentation

Robert Ieuan Palmer, Xianghua Xie Orcid Logo

Advanced Concepts for Intelligent Vision Systems, Volume: 10016, Pages: 25 - 36

Swansea University Author: Xianghua Xie Orcid Logo

DOI (Published version): 10.1007/978-3-319-48680-2_3

Abstract

In this paper we investigate the performance of NN architectures for the purpose of boundary detection, before integrating a chosen architecture in a data-driven deformable modelling framework for full segmentation.

Published in: Advanced Concepts for Intelligent Vision Systems
ISBN: 978-3-319-48679-6 978-3-319-48680-2
Published: 2016
URI: https://cronfa.swan.ac.uk/Record/cronfa32106
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spelling 2017-04-26T17:39:53.0861588 v2 32106 2017-02-24 Neural Network Boundary Detection for 3D Vessel Segmentation b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 2017-02-24 SCS In this paper we investigate the performance of NN architectures for the purpose of boundary detection, before integrating a chosen architecture in a data-driven deformable modelling framework for full segmentation. Book chapter Advanced Concepts for Intelligent Vision Systems 10016 25 36 978-3-319-48679-6 978-3-319-48680-2 Neural network, image segmentation, medical image analysis 31 10 2016 2016-10-31 10.1007/978-3-319-48680-2_3 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2017-04-26T17:39:53.0861588 2017-02-24T23:38:51.8269712 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Robert Ieuan Palmer 1 Xianghua Xie 0000-0002-2701-8660 2 0032106-21032017092225.pdf acivs16rp.pdf 2017-03-21T09:22:25.7270000 Output 2957667 application/pdf Accepted Manuscript true 2016-10-01T00:00:00.0000000 true eng
title Neural Network Boundary Detection for 3D Vessel Segmentation
spellingShingle Neural Network Boundary Detection for 3D Vessel Segmentation
Xianghua Xie
title_short Neural Network Boundary Detection for 3D Vessel Segmentation
title_full Neural Network Boundary Detection for 3D Vessel Segmentation
title_fullStr Neural Network Boundary Detection for 3D Vessel Segmentation
title_full_unstemmed Neural Network Boundary Detection for 3D Vessel Segmentation
title_sort Neural Network Boundary Detection for 3D Vessel Segmentation
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
author Xianghua Xie
author2 Robert Ieuan Palmer
Xianghua Xie
format Book chapter
container_title Advanced Concepts for Intelligent Vision Systems
container_volume 10016
container_start_page 25
publishDate 2016
institution Swansea University
isbn 978-3-319-48679-6
978-3-319-48680-2
doi_str_mv 10.1007/978-3-319-48680-2_3
college_str Faculty of Science and Engineering
hierarchytype
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
document_store_str 1
active_str 0
description In this paper we investigate the performance of NN architectures for the purpose of boundary detection, before integrating a chosen architecture in a data-driven deformable modelling framework for full segmentation.
published_date 2016-10-31T03:39:17Z
_version_ 1763751764023050240
score 11.0267

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