Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping
Purpose To develop a robust algorithm for field‐mapping in the presence of water–fat components, large B0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM). Methods A framework solving the cost‐function of th...
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Veröffentlicht in: | Magnetic resonance in medicine 2021-03, Vol.85 (3), p.1697-1712 |
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creator | Boehm, Christof Diefenbach, Maximilian N. Makowski, Marcus R. Karampinos, Dimitrios C. |
description | Purpose
To develop a robust algorithm for field‐mapping in the presence of water–fat components, large B0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM).
Methods
A framework solving the cost‐function of the water–fat separation problem in a single‐min‐cut graph‐cut based on the variable‐layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field‐mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph‐cut algorithm and a formerly proposed single‐min‐cut graph‐cut.
Results
The proposed method was shown to yield accurate field‐map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field‐map and susceptibility results compared to iterative graph‐cut field‐mapping especially in regions with low SNR, strong field‐map variations and high R2∗ values.
Conclusions
A single‐min‐cut graph‐cut field‐mapping method with a variable‐layer construction was developed for field‐mapping in body water–fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids. |
doi_str_mv | 10.1002/mrm.28515 |
format | Article |
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To develop a robust algorithm for field‐mapping in the presence of water–fat components, large B0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM).
Methods
A framework solving the cost‐function of the water–fat separation problem in a single‐min‐cut graph‐cut based on the variable‐layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field‐mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph‐cut algorithm and a formerly proposed single‐min‐cut graph‐cut.
Results
The proposed method was shown to yield accurate field‐map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field‐map and susceptibility results compared to iterative graph‐cut field‐mapping especially in regions with low SNR, strong field‐map variations and high R2∗ values.
Conclusions
A single‐min‐cut graph‐cut field‐mapping method with a variable‐layer construction was developed for field‐mapping in body water–fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.28515</identifier><identifier>PMID: 33151604</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Air bubbles ; Algorithms ; Body water ; chemical shift encoding‐based water–fat separation ; Computer Simulation ; Construction ; Dixon imaging ; Field of view ; field‐mapping ; graph‐cuts ; Image Processing, Computer-Assisted ; In vivo methods and tests ; Iterative methods ; Magnetic Resonance Imaging ; Mapping ; Mathematical analysis ; Phantoms, Imaging ; quantitative susceptibility mapping ; Robustness (mathematics) ; Simulation ; Spine ; Spine (lumbar) ; Susceptibility</subject><ispartof>Magnetic resonance in medicine, 2021-03, Vol.85 (3), p.1697-1712</ispartof><rights>2020 The Authors. published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine</rights><rights>2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.</rights><rights>Copyright Wiley Subscription Services, Inc. Mar 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3885-41974ac204bc83d80bec5a93f032ebc77dce0db50f324ca340eec29989de74ed3</citedby><cites>FETCH-LOGICAL-c3885-41974ac204bc83d80bec5a93f032ebc77dce0db50f324ca340eec29989de74ed3</cites><orcidid>0000-0002-5581-885X ; 0000-0003-1321-5804</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmrm.28515$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.28515$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33151604$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Boehm, Christof</creatorcontrib><creatorcontrib>Diefenbach, Maximilian N.</creatorcontrib><creatorcontrib>Makowski, Marcus R.</creatorcontrib><creatorcontrib>Karampinos, Dimitrios C.</creatorcontrib><title>Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping</title><title>Magnetic resonance in medicine</title><addtitle>Magn Reson Med</addtitle><description>Purpose
To develop a robust algorithm for field‐mapping in the presence of water–fat components, large B0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM).
Methods
A framework solving the cost‐function of the water–fat separation problem in a single‐min‐cut graph‐cut based on the variable‐layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field‐mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph‐cut algorithm and a formerly proposed single‐min‐cut graph‐cut.
Results
The proposed method was shown to yield accurate field‐map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field‐map and susceptibility results compared to iterative graph‐cut field‐mapping especially in regions with low SNR, strong field‐map variations and high R2∗ values.
Conclusions
A single‐min‐cut graph‐cut field‐mapping method with a variable‐layer construction was developed for field‐mapping in body water–fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids.</description><subject>Air bubbles</subject><subject>Algorithms</subject><subject>Body water</subject><subject>chemical shift encoding‐based water–fat separation</subject><subject>Computer Simulation</subject><subject>Construction</subject><subject>Dixon imaging</subject><subject>Field of view</subject><subject>field‐mapping</subject><subject>graph‐cuts</subject><subject>Image Processing, Computer-Assisted</subject><subject>In vivo methods and tests</subject><subject>Iterative methods</subject><subject>Magnetic Resonance Imaging</subject><subject>Mapping</subject><subject>Mathematical analysis</subject><subject>Phantoms, Imaging</subject><subject>quantitative susceptibility mapping</subject><subject>Robustness (mathematics)</subject><subject>Simulation</subject><subject>Spine</subject><subject>Spine (lumbar)</subject><subject>Susceptibility</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kctu1TAQhi1ERQ-FBS-ALLEpi7Tj20m8RBWXSq0qIVhHvkyKq9xqJwdl10foM_Ik-DQHFkhs7Bnr06cZ_4S8YXDGAPh5F7szXimmnpENU5wXXGn5nGyglFAIpuUxeZnSHQBoXcoX5FgIptgW5IY8XHZjHHboqR38Qu9n009hMlPYIU1zcjhOwYY2TAvtzDiG_pbahc5pXxi6MzEY2-Kvh8fWLBjp_v2p7UKfTzdP9Daa8cehboZIm4Ct3xOr7hU5akyb8PXhPiHfP338dvGluLr5fHnx4apwoqpUIVme3DgO0rpK-AosOmW0aEBwtK4svUPwVkEjuHRGSEB0XOtKeywlenFCTldvXvd-xjTVXcjrta3pcZhTzaUqdcmg2mb03T_o3TDHPk-Xqe1WlPlfRaber5SLQ0oRm3qMoTNxqRnU-1jqHEv9FEtm3x6Ms-3Q_yX_5JCB8xX4GVpc_m-qr79er8rfFrqeVw</recordid><startdate>202103</startdate><enddate>202103</enddate><creator>Boehm, Christof</creator><creator>Diefenbach, Maximilian N.</creator><creator>Makowski, Marcus R.</creator><creator>Karampinos, Dimitrios C.</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5581-885X</orcidid><orcidid>https://orcid.org/0000-0003-1321-5804</orcidid></search><sort><creationdate>202103</creationdate><title>Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping</title><author>Boehm, Christof ; Diefenbach, Maximilian N. ; Makowski, Marcus R. ; Karampinos, Dimitrios C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3885-41974ac204bc83d80bec5a93f032ebc77dce0db50f324ca340eec29989de74ed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Air bubbles</topic><topic>Algorithms</topic><topic>Body water</topic><topic>chemical shift encoding‐based water–fat separation</topic><topic>Computer Simulation</topic><topic>Construction</topic><topic>Dixon imaging</topic><topic>Field of view</topic><topic>field‐mapping</topic><topic>graph‐cuts</topic><topic>Image Processing, Computer-Assisted</topic><topic>In vivo methods and tests</topic><topic>Iterative methods</topic><topic>Magnetic Resonance Imaging</topic><topic>Mapping</topic><topic>Mathematical analysis</topic><topic>Phantoms, Imaging</topic><topic>quantitative susceptibility mapping</topic><topic>Robustness (mathematics)</topic><topic>Simulation</topic><topic>Spine</topic><topic>Spine (lumbar)</topic><topic>Susceptibility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Boehm, Christof</creatorcontrib><creatorcontrib>Diefenbach, Maximilian N.</creatorcontrib><creatorcontrib>Makowski, Marcus R.</creatorcontrib><creatorcontrib>Karampinos, Dimitrios C.</creatorcontrib><collection>Wiley Online Library (Open Access Collection)</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Boehm, Christof</au><au>Diefenbach, Maximilian N.</au><au>Makowski, Marcus R.</au><au>Karampinos, Dimitrios C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn Reson Med</addtitle><date>2021-03</date><risdate>2021</risdate><volume>85</volume><issue>3</issue><spage>1697</spage><epage>1712</epage><pages>1697-1712</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><abstract>Purpose
To develop a robust algorithm for field‐mapping in the presence of water–fat components, large B0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM).
Methods
A framework solving the cost‐function of the water–fat separation problem in a single‐min‐cut graph‐cut based on the variable‐layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field‐mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph‐cut algorithm and a formerly proposed single‐min‐cut graph‐cut.
Results
The proposed method was shown to yield accurate field‐map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field‐map and susceptibility results compared to iterative graph‐cut field‐mapping especially in regions with low SNR, strong field‐map variations and high R2∗ values.
Conclusions
A single‐min‐cut graph‐cut field‐mapping method with a variable‐layer construction was developed for field‐mapping in body water–fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>33151604</pmid><doi>10.1002/mrm.28515</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-5581-885X</orcidid><orcidid>https://orcid.org/0000-0003-1321-5804</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Air bubbles Algorithms Body water chemical shift encoding‐based water–fat separation Computer Simulation Construction Dixon imaging Field of view field‐mapping graph‐cuts Image Processing, Computer-Assisted In vivo methods and tests Iterative methods Magnetic Resonance Imaging Mapping Mathematical analysis Phantoms, Imaging quantitative susceptibility mapping Robustness (mathematics) Simulation Spine Spine (lumbar) Susceptibility |
title | Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping |
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