Regularization method for phase-constrained parallel MRI
Purpose To implement a regularization method for the phase‐constrained generalized partially parallel acquisitions (GRAPPA) algorithm to reduce image artifacts caused by data inconsistencies. Methods Phase‐constrained GRAPPA reconstructions are implemented through the use of virtual coils. To that e...
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| Veröffentlicht in: | Magnetic resonance in medicine 2014-07, Vol.72 (1), p.166-171 |
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| container_title | Magnetic resonance in medicine |
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| creator | Blaimer, Martin Jakob, Peter M. Breuer, Felix A. |
| description | Purpose
To implement a regularization method for the phase‐constrained generalized partially parallel acquisitions (GRAPPA) algorithm to reduce image artifacts caused by data inconsistencies.
Methods
Phase‐constrained GRAPPA reconstructions are implemented through the use of virtual coils. To that end, synthetic virtual coils are generated by using complex conjugate symmetric signals from the actual coils. Regularization is achieved by applying coefficient‐based penalty factors during the GRAPPA calibration procedure. Different penalizing factors are applied for the actual and virtual coils. The method is tested in vivo using T2‐weighted turbo spin echo (TSE) images.
Results
T2 signal decay perturbs conjugate k‐space symmetry and produces artifacts in phase‐constrained parallel MRI reconstructions of T2‐weighted TSE images. Using the proposed regularization method, artifacts are suppressed at the cost of noise amplification. However, there is still a significant SNR gain compared with conventional GRAPPA.
Conclusion
The proposed regularization method is an efficient approach for artifact suppression and maintains the SNR benefit of phase‐constrained parallel MRI over conventional parallel MRI. Magn Reson Med 72:166–171, 2014. © 2013 Wiley Periodicals, Inc. |
| doi_str_mv | 10.1002/mrm.24896 |
| format | Article |
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To implement a regularization method for the phase‐constrained generalized partially parallel acquisitions (GRAPPA) algorithm to reduce image artifacts caused by data inconsistencies.
Methods
Phase‐constrained GRAPPA reconstructions are implemented through the use of virtual coils. To that end, synthetic virtual coils are generated by using complex conjugate symmetric signals from the actual coils. Regularization is achieved by applying coefficient‐based penalty factors during the GRAPPA calibration procedure. Different penalizing factors are applied for the actual and virtual coils. The method is tested in vivo using T2‐weighted turbo spin echo (TSE) images.
Results
T2 signal decay perturbs conjugate k‐space symmetry and produces artifacts in phase‐constrained parallel MRI reconstructions of T2‐weighted TSE images. Using the proposed regularization method, artifacts are suppressed at the cost of noise amplification. However, there is still a significant SNR gain compared with conventional GRAPPA.
Conclusion
The proposed regularization method is an efficient approach for artifact suppression and maintains the SNR benefit of phase‐constrained parallel MRI over conventional parallel MRI. Magn Reson Med 72:166–171, 2014. © 2013 Wiley Periodicals, Inc.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.24896</identifier><identifier>PMID: 23904349</identifier><identifier>CODEN: MRMEEN</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Algorithms ; Brain Mapping - methods ; Calibration ; GRAPPA ; Healthy Volunteers ; Humans ; Image Enhancement - methods ; Image Processing, Computer-Assisted - methods ; Magnetic Resonance Imaging - instrumentation ; Magnetic Resonance Imaging - methods ; parallel MRI ; phase-constrained reconstruction ; regularization ; Signal-To-Noise Ratio</subject><ispartof>Magnetic resonance in medicine, 2014-07, Vol.72 (1), p.166-171</ispartof><rights>Copyright © 2013 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4256-90994696d21cced8f318fe45a2e670cce15ab2a7e4356643da569789ce1cb85d3</citedby></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.24896$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.24896$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23904349$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Blaimer, Martin</creatorcontrib><creatorcontrib>Jakob, Peter M.</creatorcontrib><creatorcontrib>Breuer, Felix A.</creatorcontrib><title>Regularization method for phase-constrained parallel MRI</title><title>Magnetic resonance in medicine</title><addtitle>Magn. Reson. Med</addtitle><description>Purpose
To implement a regularization method for the phase‐constrained generalized partially parallel acquisitions (GRAPPA) algorithm to reduce image artifacts caused by data inconsistencies.
Methods
Phase‐constrained GRAPPA reconstructions are implemented through the use of virtual coils. To that end, synthetic virtual coils are generated by using complex conjugate symmetric signals from the actual coils. Regularization is achieved by applying coefficient‐based penalty factors during the GRAPPA calibration procedure. Different penalizing factors are applied for the actual and virtual coils. The method is tested in vivo using T2‐weighted turbo spin echo (TSE) images.
Results
T2 signal decay perturbs conjugate k‐space symmetry and produces artifacts in phase‐constrained parallel MRI reconstructions of T2‐weighted TSE images. Using the proposed regularization method, artifacts are suppressed at the cost of noise amplification. However, there is still a significant SNR gain compared with conventional GRAPPA.
Conclusion
The proposed regularization method is an efficient approach for artifact suppression and maintains the SNR benefit of phase‐constrained parallel MRI over conventional parallel MRI. Magn Reson Med 72:166–171, 2014. © 2013 Wiley Periodicals, Inc.</description><subject>Algorithms</subject><subject>Brain Mapping - methods</subject><subject>Calibration</subject><subject>GRAPPA</subject><subject>Healthy Volunteers</subject><subject>Humans</subject><subject>Image Enhancement - methods</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Magnetic Resonance Imaging - instrumentation</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>parallel MRI</subject><subject>phase-constrained reconstruction</subject><subject>regularization</subject><subject>Signal-To-Noise Ratio</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkclOwzAQhi0EglI48AIoEhcuoV7GdnyECgpSC1IF4mi5iQOBLMVOBOXpcRd64MTJI8_3z_YjdELwBcGYDipXXVBIlNhBPcIpjSlXsIt6WAKOGVFwgA69f8MYKyVhHx1QpjAwUD2UTO1LVxpXfJu2aOqosu1rk0V546L5q_E2Tpvat84Utc2iuXGmLG0ZTaZ3R2gvN6W3x5u3j55urh-Ht_H4YXQ3vBzHKVAuYhVaglAioyRNbZbkjCS5BW6oFRKHL8LNjBppgXEhgGWGCyUTFRLpLOEZ66Pzdd25az4661tdFT61ZWlq23ReEw6AicSE_wNlkiRcEhHQsz_oW9O5OiyypJaTgIJAnW6oblbZTM9dURm30L_nC8BgDXwWpV1s8wTrpS86-KJXvujJdLIKgiJeKwrf2q-twrh3LSSTXD_fjzRhz1ePcDXUiv0AI3aMFQ</recordid><startdate>201407</startdate><enddate>201407</enddate><creator>Blaimer, Martin</creator><creator>Jakob, Peter M.</creator><creator>Breuer, Felix A.</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><scope>7QO</scope></search><sort><creationdate>201407</creationdate><title>Regularization method for phase-constrained parallel MRI</title><author>Blaimer, Martin ; Jakob, Peter M. ; Breuer, Felix A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4256-90994696d21cced8f318fe45a2e670cce15ab2a7e4356643da569789ce1cb85d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Brain Mapping - methods</topic><topic>Calibration</topic><topic>GRAPPA</topic><topic>Healthy Volunteers</topic><topic>Humans</topic><topic>Image Enhancement - methods</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Magnetic Resonance Imaging - instrumentation</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>parallel MRI</topic><topic>phase-constrained reconstruction</topic><topic>regularization</topic><topic>Signal-To-Noise Ratio</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Blaimer, Martin</creatorcontrib><creatorcontrib>Jakob, Peter M.</creatorcontrib><creatorcontrib>Breuer, Felix A.</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</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><collection>Biotechnology Research Abstracts</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Blaimer, Martin</au><au>Jakob, Peter M.</au><au>Breuer, Felix A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regularization method for phase-constrained parallel MRI</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn. Reson. Med</addtitle><date>2014-07</date><risdate>2014</risdate><volume>72</volume><issue>1</issue><spage>166</spage><epage>171</epage><pages>166-171</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><coden>MRMEEN</coden><abstract>Purpose
To implement a regularization method for the phase‐constrained generalized partially parallel acquisitions (GRAPPA) algorithm to reduce image artifacts caused by data inconsistencies.
Methods
Phase‐constrained GRAPPA reconstructions are implemented through the use of virtual coils. To that end, synthetic virtual coils are generated by using complex conjugate symmetric signals from the actual coils. Regularization is achieved by applying coefficient‐based penalty factors during the GRAPPA calibration procedure. Different penalizing factors are applied for the actual and virtual coils. The method is tested in vivo using T2‐weighted turbo spin echo (TSE) images.
Results
T2 signal decay perturbs conjugate k‐space symmetry and produces artifacts in phase‐constrained parallel MRI reconstructions of T2‐weighted TSE images. Using the proposed regularization method, artifacts are suppressed at the cost of noise amplification. However, there is still a significant SNR gain compared with conventional GRAPPA.
Conclusion
The proposed regularization method is an efficient approach for artifact suppression and maintains the SNR benefit of phase‐constrained parallel MRI over conventional parallel MRI. Magn Reson Med 72:166–171, 2014. © 2013 Wiley Periodicals, Inc.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>23904349</pmid><doi>10.1002/mrm.24896</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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| language | eng |
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| subjects | Algorithms Brain Mapping - methods Calibration GRAPPA Healthy Volunteers Humans Image Enhancement - methods Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods parallel MRI phase-constrained reconstruction regularization Signal-To-Noise Ratio |
| title | Regularization method for phase-constrained parallel MRI |
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