Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models

Abdominal aortic aneurysm (AAA) is a disease that is caused by dilation of the aortic wall. Dilation of the aortic wall will affect the size of the diameter of lumen and the aorta. In this study we use T1 and T2 images on 4 patients with AAA which generated from MR Imaging to calculate the diameter...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Scientific Journal of Informatics 2020-05, Vol.7 (1), p.66-74
1. Verfasser: Kosasih, Rifki
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 74
container_issue 1
container_start_page 66
container_title Scientific Journal of Informatics
container_volume 7
creator Kosasih, Rifki
description Abdominal aortic aneurysm (AAA) is a disease that is caused by dilation of the aortic wall. Dilation of the aortic wall will affect the size of the diameter of lumen and the aorta. In this study we use T1 and T2 images on 4 patients with AAA which generated from MR Imaging to calculate the diameter of the abdominal aortic aneurysm (AAA). To calculate the diameter of lumen and the aorta, the first step is image registration using Laplacian eigenmap method. After that we propose an automatic segmentation method on region of the aorta by using active contour models to get the contour of lumen and the aorta. The last step,  we calculate the diameter of lumen and the aorta by using contour of lumen and the aorta. In our experiment, active contour model is very good method for segmentation AAA. In the result, our proposed model give the accuracy rate of lumen is 96.41% and accuracy rate of aorta is 95.22%. 
doi_str_mv 10.15294/sji.v7i1.23625
format Article
fullrecord <record><control><sourceid>doaj_cross</sourceid><recordid>TN_cdi_crossref_primary_10_15294_sji_v7i1_23625</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_d61975a26c0f4aaeb026e3d7fc9054f0</doaj_id><sourcerecordid>oai_doaj_org_article_d61975a26c0f4aaeb026e3d7fc9054f0</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1060-a1705cce521e1349e375e2a9ed8e697fec480e98e6c430c7595ed88524c5f8673</originalsourceid><addsrcrecordid>eNo9kM1LwzAYh4soOObOXnPUQ7c3aT7aYxx-DCYedOAtZOnbkdE20nSD_fe2m3h6P3n48STJPYU5Fazgi7j386PydM4yycRVMmFcQgrA4XrsQaVKivw2mcXot8C5kiCAT5JvfehDY3vvyCfuGmz7oQ8tCRXR2zI0vrU10aEbH3SLh87HhjxorR_J04lsom93RLveH5EsQ9uHQ0feQ4l1vEtuKltHnP3VabJ5ef5avqXrj9fVUq9TR2FIaKkC4RwKRpFmvMBMCWS2wDJHWagKHc8Bi2FwPAOnRCGGUy4Yd6LKpcqmyerCLYPdm5_ON7Y7mWC9OS9CtzN2TF-jKSUtlLBMOqi4tbgFJjErVeUKELyCgbW4sFwXYuyw-udRMGfPZvBsRs_m7Dn7BX8ocJM</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models</title><source>DOAJ Directory of Open Access Journals</source><creator>Kosasih, Rifki</creator><creatorcontrib>Kosasih, Rifki</creatorcontrib><description>Abdominal aortic aneurysm (AAA) is a disease that is caused by dilation of the aortic wall. Dilation of the aortic wall will affect the size of the diameter of lumen and the aorta. In this study we use T1 and T2 images on 4 patients with AAA which generated from MR Imaging to calculate the diameter of the abdominal aortic aneurysm (AAA). To calculate the diameter of lumen and the aorta, the first step is image registration using Laplacian eigenmap method. After that we propose an automatic segmentation method on region of the aorta by using active contour models to get the contour of lumen and the aorta. The last step,  we calculate the diameter of lumen and the aorta by using contour of lumen and the aorta. In our experiment, active contour model is very good method for segmentation AAA. In the result, our proposed model give the accuracy rate of lumen is 96.41% and accuracy rate of aorta is 95.22%. </description><identifier>ISSN: 2407-7658</identifier><identifier>EISSN: 2460-0040</identifier><identifier>DOI: 10.15294/sji.v7i1.23625</identifier><language>eng</language><publisher>Jurusan Ilmu Komputer Universitas Negeri Semarang</publisher><subject>abdominal aortic aneurysm, mr imaging, laplacian eigenmap, active contour models, lumen</subject><ispartof>Scientific Journal of Informatics, 2020-05, Vol.7 (1), p.66-74</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,27923,27924</link.rule.ids></links><search><creatorcontrib>Kosasih, Rifki</creatorcontrib><title>Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models</title><title>Scientific Journal of Informatics</title><description>Abdominal aortic aneurysm (AAA) is a disease that is caused by dilation of the aortic wall. Dilation of the aortic wall will affect the size of the diameter of lumen and the aorta. In this study we use T1 and T2 images on 4 patients with AAA which generated from MR Imaging to calculate the diameter of the abdominal aortic aneurysm (AAA). To calculate the diameter of lumen and the aorta, the first step is image registration using Laplacian eigenmap method. After that we propose an automatic segmentation method on region of the aorta by using active contour models to get the contour of lumen and the aorta. The last step,  we calculate the diameter of lumen and the aorta by using contour of lumen and the aorta. In our experiment, active contour model is very good method for segmentation AAA. In the result, our proposed model give the accuracy rate of lumen is 96.41% and accuracy rate of aorta is 95.22%. </description><subject>abdominal aortic aneurysm, mr imaging, laplacian eigenmap, active contour models, lumen</subject><issn>2407-7658</issn><issn>2460-0040</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNo9kM1LwzAYh4soOObOXnPUQ7c3aT7aYxx-DCYedOAtZOnbkdE20nSD_fe2m3h6P3n48STJPYU5Fazgi7j386PydM4yycRVMmFcQgrA4XrsQaVKivw2mcXot8C5kiCAT5JvfehDY3vvyCfuGmz7oQ8tCRXR2zI0vrU10aEbH3SLh87HhjxorR_J04lsom93RLveH5EsQ9uHQ0feQ4l1vEtuKltHnP3VabJ5ef5avqXrj9fVUq9TR2FIaKkC4RwKRpFmvMBMCWS2wDJHWagKHc8Bi2FwPAOnRCGGUy4Yd6LKpcqmyerCLYPdm5_ON7Y7mWC9OS9CtzN2TF-jKSUtlLBMOqi4tbgFJjErVeUKELyCgbW4sFwXYuyw-udRMGfPZvBsRs_m7Dn7BX8ocJM</recordid><startdate>20200531</startdate><enddate>20200531</enddate><creator>Kosasih, Rifki</creator><general>Jurusan Ilmu Komputer Universitas Negeri Semarang</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20200531</creationdate><title>Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models</title><author>Kosasih, Rifki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1060-a1705cce521e1349e375e2a9ed8e697fec480e98e6c430c7595ed88524c5f8673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>abdominal aortic aneurysm, mr imaging, laplacian eigenmap, active contour models, lumen</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kosasih, Rifki</creatorcontrib><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Scientific Journal of Informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kosasih, Rifki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models</atitle><jtitle>Scientific Journal of Informatics</jtitle><date>2020-05-31</date><risdate>2020</risdate><volume>7</volume><issue>1</issue><spage>66</spage><epage>74</epage><pages>66-74</pages><issn>2407-7658</issn><eissn>2460-0040</eissn><abstract>Abdominal aortic aneurysm (AAA) is a disease that is caused by dilation of the aortic wall. Dilation of the aortic wall will affect the size of the diameter of lumen and the aorta. In this study we use T1 and T2 images on 4 patients with AAA which generated from MR Imaging to calculate the diameter of the abdominal aortic aneurysm (AAA). To calculate the diameter of lumen and the aorta, the first step is image registration using Laplacian eigenmap method. After that we propose an automatic segmentation method on region of the aorta by using active contour models to get the contour of lumen and the aorta. The last step,  we calculate the diameter of lumen and the aorta by using contour of lumen and the aorta. In our experiment, active contour model is very good method for segmentation AAA. In the result, our proposed model give the accuracy rate of lumen is 96.41% and accuracy rate of aorta is 95.22%. </abstract><pub>Jurusan Ilmu Komputer Universitas Negeri Semarang</pub><doi>10.15294/sji.v7i1.23625</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2407-7658
ispartof Scientific Journal of Informatics, 2020-05, Vol.7 (1), p.66-74
issn 2407-7658
2460-0040
language eng
recordid cdi_crossref_primary_10_15294_sji_v7i1_23625
source DOAJ Directory of Open Access Journals
subjects abdominal aortic aneurysm, mr imaging, laplacian eigenmap, active contour models, lumen
title Automatic Segmentation of Abdominal Aortic Aneurism (AAA) By Using Active Contour Models
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T02%3A29%3A34IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-doaj_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Automatic%20Segmentation%20of%20Abdominal%20Aortic%20Aneurism%20(AAA)%20By%20Using%20Active%20Contour%20Models&rft.jtitle=Scientific%20Journal%20of%20Informatics&rft.au=Kosasih,%20Rifki&rft.date=2020-05-31&rft.volume=7&rft.issue=1&rft.spage=66&rft.epage=74&rft.pages=66-74&rft.issn=2407-7658&rft.eissn=2460-0040&rft_id=info:doi/10.15294/sji.v7i1.23625&rft_dat=%3Cdoaj_cross%3Eoai_doaj_org_article_d61975a26c0f4aaeb026e3d7fc9054f0%3C/doaj_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_doaj_id=oai_doaj_org_article_d61975a26c0f4aaeb026e3d7fc9054f0&rfr_iscdi=true