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Conference Paper/Proceeding/Abstract 1190 views 231 downloads

Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images

Jingjing Deng, Xianghua Xie Orcid Logo, Louise Terry, Ashley Wood, Nick White, Tom H. Margrain, Rachel V. North

Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science., Volume: 9730, Pages: 707 - 715

Swansea University Authors: Jingjing Deng, Xianghua Xie Orcid Logo

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DOI (Published version): 10.1007/978-3-319-41501-7_79

Abstract

In this paper, we propose a machine learning based method to detect AMD and distinguish the di↵erent stages using choroidal images obtained from optical coherence tomography (OCT). We extract texture features using a Gabor filter bank and non-linear energy transformation. Then the histogram based fe...

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Published in: Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science.
ISSN: 1611-3349 0302-9743
Published: ICIAR 2016 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa32100
first_indexed 2017-03-15T20:01:45Z
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spelling 2017-11-10T13:20:52.4543486 v2 32100 2017-02-24 Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images 6f6d01d585363d6dc1622640bb4fcb3f Jingjing Deng Jingjing Deng true false b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 2017-02-24 MACS In this paper, we propose a machine learning based method to detect AMD and distinguish the di↵erent stages using choroidal images obtained from optical coherence tomography (OCT). We extract texture features using a Gabor filter bank and non-linear energy transformation. Then the histogram based feature descriptors are used to train the random forests, Support Vector Machine (SVM) and neural networks, which are tested on our choroid OCT image dataset with 21 participants. Conference Paper/Proceeding/Abstract Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science. 9730 707 715 ICIAR 2016 1611-3349 0302-9743 Medical image analysis, OCT, Neural Network 31 7 2016 2016-07-31 10.1007/978-3-319-41501-7_79 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2017-11-10T13:20:52.4543486 2017-02-24T23:12:58.4922689 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Jingjing Deng 1 Xianghua Xie 0000-0002-2701-8660 2 Louise Terry 3 Ashley Wood 4 Nick White 5 Tom H. Margrain 6 Rachel V. North 7 0032100-10112017131746.pdf jdxx.iciar2016.pdf 2017-11-10T13:17:46.3870000 Output 2054514 application/pdf Accepted Manuscript true 2017-11-10T00:00:00.0000000 true eng
title Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
spellingShingle Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
Jingjing Deng
Xianghua Xie
title_short Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
title_full Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
title_fullStr Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
title_full_unstemmed Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
title_sort Age-Related Macular Degeneration Detection and Stage Classification Using Choroidal OCT Images
author_id_str_mv 6f6d01d585363d6dc1622640bb4fcb3f
b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv 6f6d01d585363d6dc1622640bb4fcb3f_***_Jingjing Deng
b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
author Jingjing Deng
Xianghua Xie
author2 Jingjing Deng
Xianghua Xie
Louise Terry
Ashley Wood
Nick White
Tom H. Margrain
Rachel V. North
format Conference Paper/Proceeding/Abstract
container_title Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science.
container_volume 9730
container_start_page 707
publishDate 2016
institution Swansea University
issn 1611-3349
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doi_str_mv 10.1007/978-3-319-41501-7_79
publisher ICIAR 2016
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
document_store_str 1
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description In this paper, we propose a machine learning based method to detect AMD and distinguish the di↵erent stages using choroidal images obtained from optical coherence tomography (OCT). We extract texture features using a Gabor filter bank and non-linear energy transformation. Then the histogram based feature descriptors are used to train the random forests, Support Vector Machine (SVM) and neural networks, which are tested on our choroid OCT image dataset with 21 participants.
published_date 2016-07-31T04:07:46Z
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score 11.04748

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