Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images

Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs a...

Full description

Saved in:
Bibliographic Details
Main Authors: Weiguang Ding, Mei Young, Bourgault, Serge, Sieun Lee, Albiani, David A., Kirker, Andrew W., Forooghian, Farzin, Sarunic, Marinko V., Merkur, Andrew B., Beg, Mirza Faisal
Format: Conference Proceeding
Language:English
Subjects:
Adaptive optics
Biomedical optical imaging
Coherence
Image segmentation
Optical imaging
Retina
Tomography
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 7391
container_issue
container_start_page 7388
container_title
container_volume 2013
creator Weiguang Ding
Mei Young
Bourgault, Serge
Sieun Lee
Albiani, David A.
Kirker, Andrew W.
Forooghian, Farzin
Sarunic, Marinko V.
Merkur, Andrew B.
Beg, Mirza Faisal
description Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs and sub-RPE fluids are laborious and time consuming. In this paper, a novel pipeline is proposed for automatic detection of SRFs and sub-RPE fluids. First, top and bottom layers of retina are segmented using a graph cut method. Then, a Split Bregman-based segmentation method is used to segment dark regions between layers. These segmented regions are considered as potential fluid candidates, on which a set of features are generated. After that, a random forest classifier is trained to distinguish between the true fluid regions from the falsely detected fluid regions. This method shows reasonable performance in a leave-one-out evaluation using a dataset from 21 patients.
doi_str_mv 10.1109/EMBC.2013.6611265
format conference_proceeding
fullrecord <record><control><sourceid>proquest_6IE</sourceid><recordid>TN_cdi_ieee_primary_6611265</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6611265</ieee_id><sourcerecordid>1443417773</sourcerecordid><originalsourceid>FETCH-LOGICAL-i301t-5168e009bf8061df12b68fc00d54ea387fe5ab417dedb0a3b8343ebc8e237f473</originalsourceid><addsrcrecordid>eNo1kEtPwzAQhA0CUSj9AYiLj1xSvH6mx1KVh1TEBSRukZOsW6O8SByh_nuMWk67Gn0zO1pCboDNAdjifv36sJpzBmKuNQDX6oRcgVTGMA56cUouQak0kRrUWdzZQiY6NZ8TMhuGL8YYGK0FFxdkwiVANPJL8rMcQ1vb4AtaYsAi-LahraPDmPcYfGMr6qrRl9Q25Z-Y_Kud39bYBIqdDzus_FgfQR_9XcyLTNHusMemQBpvtNvedrs99bXd4nBNzp2tBpwd55R8PK7fV8_J5u3pZbXcJF4wCIkCnSJji9ylTEPpgOc6dQVjpZJoRWocKptLMCWWObMiT4UUmBcpcmGcNGJK7g65Xd9-jziErPZDgVVlG2zHIQMpRbQbIyJ6e0A9ImZdH4v2--z4afELRhxwhQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>1443417773</pqid></control><display><type>conference_proceeding</type><title>Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Weiguang Ding ; Mei Young ; Bourgault, Serge ; Sieun Lee ; Albiani, David A. ; Kirker, Andrew W. ; Forooghian, Farzin ; Sarunic, Marinko V. ; Merkur, Andrew B. ; Beg, Mirza Faisal</creator><creatorcontrib>Weiguang Ding ; Mei Young ; Bourgault, Serge ; Sieun Lee ; Albiani, David A. ; Kirker, Andrew W. ; Forooghian, Farzin ; Sarunic, Marinko V. ; Merkur, Andrew B. ; Beg, Mirza Faisal</creatorcontrib><description>Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs and sub-RPE fluids are laborious and time consuming. In this paper, a novel pipeline is proposed for automatic detection of SRFs and sub-RPE fluids. First, top and bottom layers of retina are segmented using a graph cut method. Then, a Split Bregman-based segmentation method is used to segment dark regions between layers. These segmented regions are considered as potential fluid candidates, on which a set of features are generated. After that, a random forest classifier is trained to distinguish between the true fluid regions from the falsely detected fluid regions. This method shows reasonable performance in a leave-one-out evaluation using a dataset from 21 patients.</description><identifier>ISSN: 1094-687X</identifier><identifier>EISSN: 1558-4615</identifier><identifier>EISSN: 2694-0604</identifier><identifier>EISBN: 1457702169</identifier><identifier>EISBN: 9781457702167</identifier><identifier>DOI: 10.1109/EMBC.2013.6611265</identifier><identifier>PMID: 24111452</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptive optics ; Biomedical optical imaging ; Coherence ; Image segmentation ; Optical imaging ; Retina ; Tomography</subject><ispartof>2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013, Vol.2013, p.7388-7391</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6611265$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>310,311,315,786,790,795,796,2071,27957,27958,55271</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6611265$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Weiguang Ding</creatorcontrib><creatorcontrib>Mei Young</creatorcontrib><creatorcontrib>Bourgault, Serge</creatorcontrib><creatorcontrib>Sieun Lee</creatorcontrib><creatorcontrib>Albiani, David A.</creatorcontrib><creatorcontrib>Kirker, Andrew W.</creatorcontrib><creatorcontrib>Forooghian, Farzin</creatorcontrib><creatorcontrib>Sarunic, Marinko V.</creatorcontrib><creatorcontrib>Merkur, Andrew B.</creatorcontrib><creatorcontrib>Beg, Mirza Faisal</creatorcontrib><title>Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images</title><title>2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)</title><addtitle>EMBC</addtitle><description>Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs and sub-RPE fluids are laborious and time consuming. In this paper, a novel pipeline is proposed for automatic detection of SRFs and sub-RPE fluids. First, top and bottom layers of retina are segmented using a graph cut method. Then, a Split Bregman-based segmentation method is used to segment dark regions between layers. These segmented regions are considered as potential fluid candidates, on which a set of features are generated. After that, a random forest classifier is trained to distinguish between the true fluid regions from the falsely detected fluid regions. This method shows reasonable performance in a leave-one-out evaluation using a dataset from 21 patients.</description><subject>Adaptive optics</subject><subject>Biomedical optical imaging</subject><subject>Coherence</subject><subject>Image segmentation</subject><subject>Optical imaging</subject><subject>Retina</subject><subject>Tomography</subject><issn>1094-687X</issn><issn>1558-4615</issn><issn>2694-0604</issn><isbn>1457702169</isbn><isbn>9781457702167</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kEtPwzAQhA0CUSj9AYiLj1xSvH6mx1KVh1TEBSRukZOsW6O8SByh_nuMWk67Gn0zO1pCboDNAdjifv36sJpzBmKuNQDX6oRcgVTGMA56cUouQak0kRrUWdzZQiY6NZ8TMhuGL8YYGK0FFxdkwiVANPJL8rMcQ1vb4AtaYsAi-LahraPDmPcYfGMr6qrRl9Q25Z-Y_Kud39bYBIqdDzus_FgfQR_9XcyLTNHusMemQBpvtNvedrs99bXd4nBNzp2tBpwd55R8PK7fV8_J5u3pZbXcJF4wCIkCnSJji9ylTEPpgOc6dQVjpZJoRWocKptLMCWWObMiT4UUmBcpcmGcNGJK7g65Xd9-jziErPZDgVVlG2zHIQMpRbQbIyJ6e0A9ImZdH4v2--z4afELRhxwhQ</recordid><startdate>20130101</startdate><enddate>20130101</enddate><creator>Weiguang Ding</creator><creator>Mei Young</creator><creator>Bourgault, Serge</creator><creator>Sieun Lee</creator><creator>Albiani, David A.</creator><creator>Kirker, Andrew W.</creator><creator>Forooghian, Farzin</creator><creator>Sarunic, Marinko V.</creator><creator>Merkur, Andrew B.</creator><creator>Beg, Mirza Faisal</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>7X8</scope></search><sort><creationdate>20130101</creationdate><title>Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images</title><author>Weiguang Ding ; Mei Young ; Bourgault, Serge ; Sieun Lee ; Albiani, David A. ; Kirker, Andrew W. ; Forooghian, Farzin ; Sarunic, Marinko V. ; Merkur, Andrew B. ; Beg, Mirza Faisal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i301t-5168e009bf8061df12b68fc00d54ea387fe5ab417dedb0a3b8343ebc8e237f473</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adaptive optics</topic><topic>Biomedical optical imaging</topic><topic>Coherence</topic><topic>Image segmentation</topic><topic>Optical imaging</topic><topic>Retina</topic><topic>Tomography</topic><toplevel>online_resources</toplevel><creatorcontrib>Weiguang Ding</creatorcontrib><creatorcontrib>Mei Young</creatorcontrib><creatorcontrib>Bourgault, Serge</creatorcontrib><creatorcontrib>Sieun Lee</creatorcontrib><creatorcontrib>Albiani, David A.</creatorcontrib><creatorcontrib>Kirker, Andrew W.</creatorcontrib><creatorcontrib>Forooghian, Farzin</creatorcontrib><creatorcontrib>Sarunic, Marinko V.</creatorcontrib><creatorcontrib>Merkur, Andrew B.</creatorcontrib><creatorcontrib>Beg, Mirza Faisal</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>MEDLINE - Academic</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Weiguang Ding</au><au>Mei Young</au><au>Bourgault, Serge</au><au>Sieun Lee</au><au>Albiani, David A.</au><au>Kirker, Andrew W.</au><au>Forooghian, Farzin</au><au>Sarunic, Marinko V.</au><au>Merkur, Andrew B.</au><au>Beg, Mirza Faisal</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images</atitle><btitle>2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)</btitle><stitle>EMBC</stitle><date>2013-01-01</date><risdate>2013</risdate><volume>2013</volume><spage>7388</spage><epage>7391</epage><pages>7388-7391</pages><issn>1094-687X</issn><eissn>1558-4615</eissn><eissn>2694-0604</eissn><eisbn>1457702169</eisbn><eisbn>9781457702167</eisbn><notes>ObjectType-Article-1</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-2</notes><notes>content type line 23</notes><abstract>Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs and sub-RPE fluids are laborious and time consuming. In this paper, a novel pipeline is proposed for automatic detection of SRFs and sub-RPE fluids. First, top and bottom layers of retina are segmented using a graph cut method. Then, a Split Bregman-based segmentation method is used to segment dark regions between layers. These segmented regions are considered as potential fluid candidates, on which a set of features are generated. After that, a random forest classifier is trained to distinguish between the true fluid regions from the falsely detected fluid regions. This method shows reasonable performance in a leave-one-out evaluation using a dataset from 21 patients.</abstract><pub>IEEE</pub><pmid>24111452</pmid><doi>10.1109/EMBC.2013.6611265</doi><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1094-687X
ispartof 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013, Vol.2013, p.7388-7391
issn 1094-687X
1558-4615
2694-0604
language eng
recordid cdi_ieee_primary_6611265
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Adaptive optics
Biomedical optical imaging
Coherence
Image segmentation
Optical imaging
Retina
Tomography
title Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-09-22T07%3A41%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Automatic%20detection%20of%20subretinal%20fluid%20and%20sub-retinal%20pigment%20epithelium%20fluid%20in%20optical%20coherence%20tomography%20images&rft.btitle=2013%2035th%20Annual%20International%20Conference%20of%20the%20IEEE%20Engineering%20in%20Medicine%20and%20Biology%20Society%20(EMBC)&rft.au=Weiguang%20Ding&rft.date=2013-01-01&rft.volume=2013&rft.spage=7388&rft.epage=7391&rft.pages=7388-7391&rft.issn=1094-687X&rft.eissn=1558-4615&rft_id=info:doi/10.1109/EMBC.2013.6611265&rft.eisbn=1457702169&rft.eisbn_list=9781457702167&rft_dat=%3Cproquest_6IE%3E1443417773%3C/proquest_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i301t-5168e009bf8061df12b68fc00d54ea387fe5ab417dedb0a3b8343ebc8e237f473%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1443417773&rft_id=info:pmid/24111452&rft_ieee_id=6611265&rfr_iscdi=true