Monitored Reconstruction: Computed Tomography as an Anytime Algorithm

Computed tomography is an important technique for non-destructive analysis of an object's internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the ti...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE access 2020, Vol.8, p.110759-110774
Hauptverfasser: Bulatov, Konstantin, Chukalina, Marina, Buzmakov, Alexey, Nikolaev, Dmitry, Arlazarov, Vladimir V.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 110774
container_issue
container_start_page 110759
container_title IEEE access
container_volume 8
creator Bulatov, Konstantin
Chukalina, Marina
Buzmakov, Alexey
Nikolaev, Dmitry
Arlazarov, Vladimir V.
description Computed tomography is an important technique for non-destructive analysis of an object's internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality.
doi_str_mv 10.1109/ACCESS.2020.3002019
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2454616938</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9115485</ieee_id><doaj_id>oai_doaj_org_article_3d05fc7c2eea403d96ac132b1dde902c</doaj_id><sourcerecordid>2454616938</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-628271c54deebf46e93a15737e3a890f46af6104d8b15f3c8b7fe09d3961f3ad3</originalsourceid><addsrcrecordid>eNpNkF9LwzAUxYMoOHSfYC8Fnzvzp2kb30qZOpgIbj6HNLndOtamptnDvr2ZHcM83FzOveck_BCaETwnBIvnoiwX6_WcYornDIdKxA2aUJKKmHGW3v7r79F0GPY4nDxIPJugxYftGm8dmOgLtO0G747aN7Z7iUrb9kcfBhvb2q1T_e4UqSFSXVR0J9-0EBWHrXWN37WP6K5WhwGml_sBfb8uNuV7vPp8W5bFKtYJzn2c0pxmRPPEAFR1koJgivCMZcBULnBQVJ0SnJi8IrxmOq-yGrAwTKSkZsqwB7Qcc41Ve9m7plXuJK1q5J9g3VYq5xt9AMkM5rXONAVQCWZGpEoTRitiDAhMdch6GrN6Z3-OMHi5t0fXhe9LmvAkDYBYHrbYuKWdHQYH9fVVguUZvxzxyzN-ecEfXLPR1QDA1SEI4UnO2S-CWoCZ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2454616938</pqid></control><display><type>article</type><title>Monitored Reconstruction: Computed Tomography as an Anytime Algorithm</title><source>IEEE Open Access Journals</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Bulatov, Konstantin ; Chukalina, Marina ; Buzmakov, Alexey ; Nikolaev, Dmitry ; Arlazarov, Vladimir V.</creator><creatorcontrib>Bulatov, Konstantin ; Chukalina, Marina ; Buzmakov, Alexey ; Nikolaev, Dmitry ; Arlazarov, Vladimir V.</creatorcontrib><description>Computed tomography is an important technique for non-destructive analysis of an object's internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2020.3002019</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Algorithms ; Anytime algorithms ; Computed tomography ; dose reduction ; Image reconstruction ; Medical diagnostic imaging ; monitored reconstruction ; Monitoring ; Nondestructive testing ; optimal stopping ; Radiation dosage ; Tomography ; X-ray imaging ; X-ray tomography</subject><ispartof>IEEE access, 2020, Vol.8, p.110759-110774</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-628271c54deebf46e93a15737e3a890f46af6104d8b15f3c8b7fe09d3961f3ad3</citedby><cites>FETCH-LOGICAL-c408t-628271c54deebf46e93a15737e3a890f46af6104d8b15f3c8b7fe09d3961f3ad3</cites><orcidid>0000-0003-1644-5162 ; 0000-0003-0539-5606 ; 0000-0003-3260-9104 ; 0000-0002-1410-5175 ; 0000-0001-5560-7668</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9115485$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2095,4009,27612,27902,27903,27904,54911</link.rule.ids></links><search><creatorcontrib>Bulatov, Konstantin</creatorcontrib><creatorcontrib>Chukalina, Marina</creatorcontrib><creatorcontrib>Buzmakov, Alexey</creatorcontrib><creatorcontrib>Nikolaev, Dmitry</creatorcontrib><creatorcontrib>Arlazarov, Vladimir V.</creatorcontrib><title>Monitored Reconstruction: Computed Tomography as an Anytime Algorithm</title><title>IEEE access</title><addtitle>Access</addtitle><description>Computed tomography is an important technique for non-destructive analysis of an object's internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality.</description><subject>Algorithms</subject><subject>Anytime algorithms</subject><subject>Computed tomography</subject><subject>dose reduction</subject><subject>Image reconstruction</subject><subject>Medical diagnostic imaging</subject><subject>monitored reconstruction</subject><subject>Monitoring</subject><subject>Nondestructive testing</subject><subject>optimal stopping</subject><subject>Radiation dosage</subject><subject>Tomography</subject><subject>X-ray imaging</subject><subject>X-ray tomography</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNkF9LwzAUxYMoOHSfYC8Fnzvzp2kb30qZOpgIbj6HNLndOtamptnDvr2ZHcM83FzOveck_BCaETwnBIvnoiwX6_WcYornDIdKxA2aUJKKmHGW3v7r79F0GPY4nDxIPJugxYftGm8dmOgLtO0G747aN7Z7iUrb9kcfBhvb2q1T_e4UqSFSXVR0J9-0EBWHrXWN37WP6K5WhwGml_sBfb8uNuV7vPp8W5bFKtYJzn2c0pxmRPPEAFR1koJgivCMZcBULnBQVJ0SnJi8IrxmOq-yGrAwTKSkZsqwB7Qcc41Ve9m7plXuJK1q5J9g3VYq5xt9AMkM5rXONAVQCWZGpEoTRitiDAhMdch6GrN6Z3-OMHi5t0fXhe9LmvAkDYBYHrbYuKWdHQYH9fVVguUZvxzxyzN-ecEfXLPR1QDA1SEI4UnO2S-CWoCZ</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Bulatov, Konstantin</creator><creator>Chukalina, Marina</creator><creator>Buzmakov, Alexey</creator><creator>Nikolaev, Dmitry</creator><creator>Arlazarov, Vladimir V.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1644-5162</orcidid><orcidid>https://orcid.org/0000-0003-0539-5606</orcidid><orcidid>https://orcid.org/0000-0003-3260-9104</orcidid><orcidid>https://orcid.org/0000-0002-1410-5175</orcidid><orcidid>https://orcid.org/0000-0001-5560-7668</orcidid></search><sort><creationdate>2020</creationdate><title>Monitored Reconstruction: Computed Tomography as an Anytime Algorithm</title><author>Bulatov, Konstantin ; Chukalina, Marina ; Buzmakov, Alexey ; Nikolaev, Dmitry ; Arlazarov, Vladimir V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-628271c54deebf46e93a15737e3a890f46af6104d8b15f3c8b7fe09d3961f3ad3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Anytime algorithms</topic><topic>Computed tomography</topic><topic>dose reduction</topic><topic>Image reconstruction</topic><topic>Medical diagnostic imaging</topic><topic>monitored reconstruction</topic><topic>Monitoring</topic><topic>Nondestructive testing</topic><topic>optimal stopping</topic><topic>Radiation dosage</topic><topic>Tomography</topic><topic>X-ray imaging</topic><topic>X-ray tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bulatov, Konstantin</creatorcontrib><creatorcontrib>Chukalina, Marina</creatorcontrib><creatorcontrib>Buzmakov, Alexey</creatorcontrib><creatorcontrib>Nikolaev, Dmitry</creatorcontrib><creatorcontrib>Arlazarov, Vladimir V.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bulatov, Konstantin</au><au>Chukalina, Marina</au><au>Buzmakov, Alexey</au><au>Nikolaev, Dmitry</au><au>Arlazarov, Vladimir V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Monitored Reconstruction: Computed Tomography as an Anytime Algorithm</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2020</date><risdate>2020</risdate><volume>8</volume><spage>110759</spage><epage>110774</epage><pages>110759-110774</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Computed tomography is an important technique for non-destructive analysis of an object's internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2020.3002019</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0003-1644-5162</orcidid><orcidid>https://orcid.org/0000-0003-0539-5606</orcidid><orcidid>https://orcid.org/0000-0003-3260-9104</orcidid><orcidid>https://orcid.org/0000-0002-1410-5175</orcidid><orcidid>https://orcid.org/0000-0001-5560-7668</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2169-3536
ispartof IEEE access, 2020, Vol.8, p.110759-110774
issn 2169-3536
2169-3536
language eng
recordid cdi_proquest_journals_2454616938
source IEEE Open Access Journals; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Algorithms
Anytime algorithms
Computed tomography
dose reduction
Image reconstruction
Medical diagnostic imaging
monitored reconstruction
Monitoring
Nondestructive testing
optimal stopping
Radiation dosage
Tomography
X-ray imaging
X-ray tomography
title Monitored Reconstruction: Computed Tomography as an Anytime Algorithm
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T18%3A31%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Monitored%20Reconstruction:%20Computed%20Tomography%20as%20an%20Anytime%20Algorithm&rft.jtitle=IEEE%20access&rft.au=Bulatov,%20Konstantin&rft.date=2020&rft.volume=8&rft.spage=110759&rft.epage=110774&rft.pages=110759-110774&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2020.3002019&rft_dat=%3Cproquest_cross%3E2454616938%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2454616938&rft_id=info:pmid/&rft_ieee_id=9115485&rft_doaj_id=oai_doaj_org_article_3d05fc7c2eea403d96ac132b1dde902c&rfr_iscdi=true