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Combining region-based and imprecise boundary-based cues for interactive medical image segmentation

Jonathan-lee Jones, Xianghua Xie Orcid Logo, Ehab Essa

International Journal for Numerical Methods in Biomedical Engineering, Volume: 30, Issue: 12, Pages: 1649 - 1666

Swansea University Authors: Jonathan-lee Jones, Xianghua Xie Orcid Logo

DOI (Published version): 10.1002/cnm.2693

Abstract

We present an approach combining both region selection and user point selection for user- assisted segmentation as either an enclosed object or an open curve, investigate the method of image segmentation in specific medical applications (user-assisted segmentation of the media–adventitia border in i...

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Published in: International Journal for Numerical Methods in Biomedical Engineering
Published: 2014
URI: https://cronfa.swan.ac.uk/Record/cronfa20986
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spelling 2019-06-04T17:06:49.4415373 v2 20986 2015-04-29 Combining region-based and imprecise boundary-based cues for interactive medical image segmentation 9fb5e49002a9ebb15f1fdbe60df1dbdf Jonathan-lee Jones Jonathan-lee Jones true false b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 2015-04-29 SBI We present an approach combining both region selection and user point selection for user- assisted segmentation as either an enclosed object or an open curve, investigate the method of image segmentation in specific medical applications (user-assisted segmentation of the media–adventitia border in intravascular ultrasound images, and lumen border in optical coherence tomography images), and then demonstrate the method with generic images to show how it could be utilized in other types of medical image and is not limited to the applications described. The proposed method combines point-based soft con- straint on object boundary and stroke-based regional constraint. The user points act as attraction points and are treated as soft constraints rather than hard constraints that the segmented boundary has to pass through. The user can also use strokes to specify region of interest. The probabilities of region of interest for each pixel are then calculated, and their discontinuity is used to indicate object boundary. The combinations of different types of user constraints and image features allow flexible and robust segmentation, which is formulated as an energy minimization problem on a multilayered graph and is solved using a shortest path search algorithm. We show that this combinatorial approach allows efficient and effective interactive segmentation, which can be used with both open and closed curves to segment a variety of images in different ways. The proposed method is demonstrated in the two medical applications, that is, intravascular ultrasound and optical coherence tomography images, where image artefacts such as acoustic shadow and calcification are commonplace and thus user guidance is desirable. We carried out both qualitative and quantitative analysis of the results for the medical data; comparing the proposed method against a number of interactive segmentation techniques. Journal Article International Journal for Numerical Methods in Biomedical Engineering 30 12 1649 1666 Image segmentation, medical image analysis, interactive segmentation 31 12 2014 2014-12-31 10.1002/cnm.2693 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University 2019-06-04T17:06:49.4415373 2015-04-29T17:35:19.1205177 College of Science Computer Science Jonathan-lee Jones 1 Xianghua Xie 0000-0002-2701-8660 2 Ehab Essa 3 0020986-29042015173606.pdf cnm2693.pdf 2015-04-29T17:36:06.0170000 Output 5810975 application/pdf Version of Record true 2015-04-29T00:00:00.0000000 true
title Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
spellingShingle Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
Jonathan-lee Jones
Xianghua Xie
title_short Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
title_full Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
title_fullStr Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
title_full_unstemmed Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
title_sort Combining region-based and imprecise boundary-based cues for interactive medical image segmentation
author_id_str_mv 9fb5e49002a9ebb15f1fdbe60df1dbdf
b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv 9fb5e49002a9ebb15f1fdbe60df1dbdf_***_Jonathan-lee Jones
b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
author Jonathan-lee Jones
Xianghua Xie
author2 Jonathan-lee Jones
Xianghua Xie
Ehab Essa
format Journal article
container_title International Journal for Numerical Methods in Biomedical Engineering
container_volume 30
container_issue 12
container_start_page 1649
publishDate 2014
institution Swansea University
doi_str_mv 10.1002/cnm.2693
college_str College of Science
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hierarchy_parent_id collegeofscience
hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
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description We present an approach combining both region selection and user point selection for user- assisted segmentation as either an enclosed object or an open curve, investigate the method of image segmentation in specific medical applications (user-assisted segmentation of the media–adventitia border in intravascular ultrasound images, and lumen border in optical coherence tomography images), and then demonstrate the method with generic images to show how it could be utilized in other types of medical image and is not limited to the applications described. The proposed method combines point-based soft con- straint on object boundary and stroke-based regional constraint. The user points act as attraction points and are treated as soft constraints rather than hard constraints that the segmented boundary has to pass through. The user can also use strokes to specify region of interest. The probabilities of region of interest for each pixel are then calculated, and their discontinuity is used to indicate object boundary. The combinations of different types of user constraints and image features allow flexible and robust segmentation, which is formulated as an energy minimization problem on a multilayered graph and is solved using a shortest path search algorithm. We show that this combinatorial approach allows efficient and effective interactive segmentation, which can be used with both open and closed curves to segment a variety of images in different ways. The proposed method is demonstrated in the two medical applications, that is, intravascular ultrasound and optical coherence tomography images, where image artefacts such as acoustic shadow and calcification are commonplace and thus user guidance is desirable. We carried out both qualitative and quantitative analysis of the results for the medical data; comparing the proposed method against a number of interactive segmentation techniques.
published_date 2014-12-31T03:31:21Z
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