Journal article 1245 views 319 downloads
Registration and Modeling from Spaced and Misaligned Image Volumes
IEEE Transactions on Image Processing, Volume: 25, Issue: 9, Pages: 4379 - 4393
Swansea University Authors: Adeline Paiement, Xianghua Xie
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DOI (Published version): 10.1109/TIP.2016.2586660
Abstract
We present an integrated registration, segmentation, and shape interpolation framework to model objects from 3D and 4D volumes made up of spaced and misaligned slices having arbitrary relative positions. The framework was validated on artificial data and tested on real MRI and CT scans. The complete...
Published in: | IEEE Transactions on Image Processing |
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ISSN: | 1941-0042 |
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(IEEE) Institute of Electrical and Electronics Engineers
2016
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URI: | https://cronfa.swan.ac.uk/Record/cronfa28997 |
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2021-01-28T16:09:02.7030044 v2 28997 2016-06-27 Registration and Modeling from Spaced and Misaligned Image Volumes f50adf4186d930e3a2a0f9a6d643cf53 Adeline Paiement Adeline Paiement true false b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 2016-06-27 FGHSS We present an integrated registration, segmentation, and shape interpolation framework to model objects from 3D and 4D volumes made up of spaced and misaligned slices having arbitrary relative positions. The framework was validated on artificial data and tested on real MRI and CT scans. The complete framework performed significantly better than the sequential approach of registration followed by segmentation and shape interpo- lation. Journal Article IEEE Transactions on Image Processing 25 9 4379 4393 (IEEE) Institute of Electrical and Electronics Engineers 1941-0042 Modeling methodologies, registration, segmentation, shape interpolation, level set methods, RBF. 1 9 2016 2016-09-01 10.1109/TIP.2016.2586660 COLLEGE NANME Humanities and Social Sciences - Faculty COLLEGE CODE FGHSS Swansea University 2021-01-28T16:09:02.7030044 2016-06-27T14:12:04.4637156 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Adeline Paiement 1 Majid Mirmehdi 2 Xianghua Xie 0000-0002-2701-8660 3 Mark C. K. Hamilton 4 0028997-27062016141637.pdf camera_ready.pdf 2016-06-27T14:16:37.2170000 Output 5026841 application/pdf Accepted Manuscript true true eng |
title |
Registration and Modeling from Spaced and Misaligned Image Volumes |
spellingShingle |
Registration and Modeling from Spaced and Misaligned Image Volumes Adeline Paiement Xianghua Xie |
title_short |
Registration and Modeling from Spaced and Misaligned Image Volumes |
title_full |
Registration and Modeling from Spaced and Misaligned Image Volumes |
title_fullStr |
Registration and Modeling from Spaced and Misaligned Image Volumes |
title_full_unstemmed |
Registration and Modeling from Spaced and Misaligned Image Volumes |
title_sort |
Registration and Modeling from Spaced and Misaligned Image Volumes |
author_id_str_mv |
f50adf4186d930e3a2a0f9a6d643cf53 b334d40963c7a2f435f06d2c26c74e11 |
author_id_fullname_str_mv |
f50adf4186d930e3a2a0f9a6d643cf53_***_Adeline Paiement b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie |
author |
Adeline Paiement Xianghua Xie |
author2 |
Adeline Paiement Majid Mirmehdi Xianghua Xie Mark C. K. Hamilton |
format |
Journal article |
container_title |
IEEE Transactions on Image Processing |
container_volume |
25 |
container_issue |
9 |
container_start_page |
4379 |
publishDate |
2016 |
institution |
Swansea University |
issn |
1941-0042 |
doi_str_mv |
10.1109/TIP.2016.2586660 |
publisher |
(IEEE) Institute of Electrical and Electronics Engineers |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science |
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description |
We present an integrated registration, segmentation, and shape interpolation framework to model objects from 3D and 4D volumes made up of spaced and misaligned slices having arbitrary relative positions. The framework was validated on artificial data and tested on real MRI and CT scans. The complete framework performed significantly better than the sequential approach of registration followed by segmentation and shape interpo- lation. |
published_date |
2016-09-01T03:35:22Z |
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1763751517447258112 |
score |
11.035634 |