High-resolution, large dynamic range field map estimation
Purpose We present a theory and a corresponding method to compute high‐resolution field maps over a large dynamic range. Theory and Methods We derive a closed‐form expression for the error in the field map value when computed from two echoes. We formulate an optimization problem to choose three echo...
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Veröffentlicht in: | Magnetic resonance in medicine 2014-01, Vol.71 (1), p.105-117 |
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container_title | Magnetic resonance in medicine |
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creator | Dagher, Joseph Reese, Timothy Bilgin, Ali |
description | Purpose
We present a theory and a corresponding method to compute high‐resolution field maps over a large dynamic range.
Theory and Methods
We derive a closed‐form expression for the error in the field map value when computed from two echoes. We formulate an optimization problem to choose three echo times which result in a pair of maximally distinct error distributions. We use standard field mapping sequences at the prescribed echo times. We then design a corresponding estimation algorithm which takes advantage of the optimized echo times to disambiguate the field offset value.
Results
We validate our method using high‐resolution images of a phantom at 7T. The resulting field maps demonstrate robust mapping over both a large dynamic range, and in low SNR regions. We also present high‐resolution offset maps in vivo using both, GRE and multiecho gradient echo sequences. Even though the proposed echo time spacings are larger than the well known phase aliasing cutoff, the resulting field maps exhibit a large dynamic range without the use of phase unwrapping or spatial regularization techniques.
Conclusion
We demonstrate a novel three‐echo field map estimation method which overcomes the traditional noise‐dynamic range trade‐off. Magn Reson Med 71:105–117, 2014. © 2013 Wiley Periodicals, Inc. |
doi_str_mv | 10.1002/mrm.24636 |
format | Article |
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We present a theory and a corresponding method to compute high‐resolution field maps over a large dynamic range.
Theory and Methods
We derive a closed‐form expression for the error in the field map value when computed from two echoes. We formulate an optimization problem to choose three echo times which result in a pair of maximally distinct error distributions. We use standard field mapping sequences at the prescribed echo times. We then design a corresponding estimation algorithm which takes advantage of the optimized echo times to disambiguate the field offset value.
Results
We validate our method using high‐resolution images of a phantom at 7T. The resulting field maps demonstrate robust mapping over both a large dynamic range, and in low SNR regions. We also present high‐resolution offset maps in vivo using both, GRE and multiecho gradient echo sequences. Even though the proposed echo time spacings are larger than the well known phase aliasing cutoff, the resulting field maps exhibit a large dynamic range without the use of phase unwrapping or spatial regularization techniques.
Conclusion
We demonstrate a novel three‐echo field map estimation method which overcomes the traditional noise‐dynamic range trade‐off. Magn Reson Med 71:105–117, 2014. © 2013 Wiley Periodicals, Inc.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.24636</identifier><identifier>PMID: 23401245</identifier><identifier>CODEN: MRMEEN</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Algorithms ; Ankle Joint - anatomy & histology ; Ankle Joint - physiology ; Brain - anatomy & histology ; Brain - physiology ; Brain Mapping - methods ; Female ; field inhomogeneity ; field map estimation ; Humans ; Image Interpretation, Computer-Assisted - methods ; Magnetic Fields ; Magnetic Resonance Imaging - methods ; Male ; MR phase ; phase unwrapping ; Radiometry - methods ; Reproducibility of Results ; Sensitivity and Specificity</subject><ispartof>Magnetic resonance in medicine, 2014-01, Vol.71 (1), p.105-117</ispartof><rights>Copyright © 2013 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5146-b3d3c6c35e58f52c08e4b24cea8bcee2887f57f118146876db5a62ddae8f73123</citedby><cites>FETCH-LOGICAL-c5146-b3d3c6c35e58f52c08e4b24cea8bcee2887f57f118146876db5a62ddae8f73123</cites></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.24636$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.24636$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,1433,27923,27924,45573,45574,46408,46832</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23401245$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dagher, Joseph</creatorcontrib><creatorcontrib>Reese, Timothy</creatorcontrib><creatorcontrib>Bilgin, Ali</creatorcontrib><title>High-resolution, large dynamic range field map estimation</title><title>Magnetic resonance in medicine</title><addtitle>Magn. Reson. Med</addtitle><description>Purpose
We present a theory and a corresponding method to compute high‐resolution field maps over a large dynamic range.
Theory and Methods
We derive a closed‐form expression for the error in the field map value when computed from two echoes. We formulate an optimization problem to choose three echo times which result in a pair of maximally distinct error distributions. We use standard field mapping sequences at the prescribed echo times. We then design a corresponding estimation algorithm which takes advantage of the optimized echo times to disambiguate the field offset value.
Results
We validate our method using high‐resolution images of a phantom at 7T. The resulting field maps demonstrate robust mapping over both a large dynamic range, and in low SNR regions. We also present high‐resolution offset maps in vivo using both, GRE and multiecho gradient echo sequences. Even though the proposed echo time spacings are larger than the well known phase aliasing cutoff, the resulting field maps exhibit a large dynamic range without the use of phase unwrapping or spatial regularization techniques.
Conclusion
We demonstrate a novel three‐echo field map estimation method which overcomes the traditional noise‐dynamic range trade‐off. Magn Reson Med 71:105–117, 2014. © 2013 Wiley Periodicals, Inc.</description><subject>Algorithms</subject><subject>Ankle Joint - anatomy & histology</subject><subject>Ankle Joint - physiology</subject><subject>Brain - anatomy & histology</subject><subject>Brain - physiology</subject><subject>Brain Mapping - methods</subject><subject>Female</subject><subject>field inhomogeneity</subject><subject>field map estimation</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Magnetic Fields</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>MR phase</subject><subject>phase unwrapping</subject><subject>Radiometry - methods</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</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>eNqNkV1rFDEUhkNR7LZ64R8oA9604LT5_rgplEVbsa0oFsWbkMmc2abOx5rsqPvvzbrt0hYEr0LIc56cc16EXhJ8SDCmR13sDimXTG6hCRGUllQY_gRNsOK4ZMTwbbST0g3G2BjFn6FtyjgmlIsJMmdhdl1GSEM7LsLQvy5aF2dQ1MvedcEX0fX51gRo66Jz8wLSInRuRT5HTxvXJnhxe-6iq7dvPk_PyvMPp--mJ-elF4TLsmI189IzAUI3gnqsgVeUe3C68gBUa9UI1RCiM62VrCvhJK1rB7pRjFC2i47X3vlYdVB76BfRtXYecx9xaQcX7MOXPlzb2fDTMkMMYSoL9m8Fcfgx5gFsF5KHtnU9DGOyhBsqJaGY_AcqjRQyrzijrx6hN8MY-7yJFaVl_pvqTB2sKR-HlCI0m74JtqvsbM7O_s0us3v3B92Qd2Fl4GgN_AotLP9tshefLu6U5boipAX83lS4-N1KxZSwXy5P7bfp9PLre67sR_YHIv-xtQ</recordid><startdate>201401</startdate><enddate>201401</enddate><creator>Dagher, Joseph</creator><creator>Reese, Timothy</creator><creator>Bilgin, Ali</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>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><scope>7QO</scope><scope>5PM</scope></search><sort><creationdate>201401</creationdate><title>High-resolution, large dynamic range field map estimation</title><author>Dagher, Joseph ; Reese, Timothy ; Bilgin, Ali</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5146-b3d3c6c35e58f52c08e4b24cea8bcee2887f57f118146876db5a62ddae8f73123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Ankle Joint - anatomy & histology</topic><topic>Ankle Joint - physiology</topic><topic>Brain - anatomy & histology</topic><topic>Brain - physiology</topic><topic>Brain Mapping - methods</topic><topic>Female</topic><topic>field inhomogeneity</topic><topic>field map estimation</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Magnetic Fields</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>MR phase</topic><topic>phase unwrapping</topic><topic>Radiometry - methods</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dagher, Joseph</creatorcontrib><creatorcontrib>Reese, Timothy</creatorcontrib><creatorcontrib>Bilgin, Ali</creatorcontrib><collection>Istex</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><collection>Biotechnology Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dagher, Joseph</au><au>Reese, Timothy</au><au>Bilgin, Ali</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>High-resolution, large dynamic range field map estimation</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn. Reson. Med</addtitle><date>2014-01</date><risdate>2014</risdate><volume>71</volume><issue>1</issue><spage>105</spage><epage>117</epage><pages>105-117</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><coden>MRMEEN</coden><abstract>Purpose
We present a theory and a corresponding method to compute high‐resolution field maps over a large dynamic range.
Theory and Methods
We derive a closed‐form expression for the error in the field map value when computed from two echoes. We formulate an optimization problem to choose three echo times which result in a pair of maximally distinct error distributions. We use standard field mapping sequences at the prescribed echo times. We then design a corresponding estimation algorithm which takes advantage of the optimized echo times to disambiguate the field offset value.
Results
We validate our method using high‐resolution images of a phantom at 7T. The resulting field maps demonstrate robust mapping over both a large dynamic range, and in low SNR regions. We also present high‐resolution offset maps in vivo using both, GRE and multiecho gradient echo sequences. Even though the proposed echo time spacings are larger than the well known phase aliasing cutoff, the resulting field maps exhibit a large dynamic range without the use of phase unwrapping or spatial regularization techniques.
Conclusion
We demonstrate a novel three‐echo field map estimation method which overcomes the traditional noise‐dynamic range trade‐off. Magn Reson Med 71:105–117, 2014. © 2013 Wiley Periodicals, Inc.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>23401245</pmid><doi>10.1002/mrm.24636</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Ankle Joint - anatomy & histology Ankle Joint - physiology Brain - anatomy & histology Brain - physiology Brain Mapping - methods Female field inhomogeneity field map estimation Humans Image Interpretation, Computer-Assisted - methods Magnetic Fields Magnetic Resonance Imaging - methods Male MR phase phase unwrapping Radiometry - methods Reproducibility of Results Sensitivity and Specificity |
title | High-resolution, large dynamic range field map estimation |
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