SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space
A new approach to autocalibrating, coil‐by‐coil parallel imaging reconstruction, is presented. It is a generalized reconstruction framework based on self‐consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisi...
Gespeichert in:
| Veröffentlicht in: | Magnetic resonance in medicine 2010-08, Vol.64 (2), p.457-471 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 471 |
|---|---|
| container_issue | 2 |
| container_start_page | 457 |
| container_title | Magnetic resonance in medicine |
| container_volume | 64 |
| creator | Lustig, Michael Pauly, John M. |
| description | A new approach to autocalibrating, coil‐by‐coil parallel imaging reconstruction, is presented. It is a generalized reconstruction framework based on self‐consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k‐space sampling patterns. The formulation can flexibly incorporate additional image priors such as off‐resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k‐space domain are presented. These are based on a projection over convex sets and conjugate gradient algorithms. Phantom and in vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off‐resonance correction and nonlinear ℓ1‐wavelet regularization are also demonstrated. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc. |
| doi_str_mv | 10.1002/mrm.22428 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2925465</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2453160946</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5788-353e65dc61faa11a865e8a7938a6ea63092b9144f6ce954158ed682df3ab87663</originalsourceid><addsrcrecordid>eNqFkU1rFEEQhhtRzBo9-AdkwIPkMEl_f3gQJCRxJVGJEcVLUztbs3YyM712z0T33zubTRYVxFMf6qmXp-sl5Cmj-4xSftCmdp9zye09MmGK85IrJ--TCTWSloI5uUMe5XxJKXXOyIdkh1OtlXF0Qr58_DA9Dxcvi2mPCfpwjUXGpi6r2OWQe-z6YgkJmgabIrSwCN2iSLie9mmo-hC7ok6xLSDNQp8grYqrMi-hwsfkQQ1Nxie37y75dHx0cfimPH1_Mj18fVpWylhbCiVQq3mlWQ3AGFit0IJxwoJG0II6PnNMylpX6JRkyuJcWz6vBcys0Vrskleb3OUwa3Fejcajrl-m0TatfITg_5x04ZtfxGvPHVdSqzHgxW1Ait8HzL1vQ66waaDDOGRvraCSKir_SxppneBMrqWe_0VexiF14x08l0owTd0NtbehqhRzTlhvrRn162L9WKy_KXZkn_3-zS151-QIHGyAH6HB1b-T_Nn52V1kudlY9_xzuwHpymsjjPKf3514e_xWia-WeyZ-AcGwvFU</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2453160946</pqid></control><display><type>article</type><title>SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space</title><source>MEDLINE</source><source>Access via Wiley Online Library</source><source>Wiley Online Library (Open Access Collection)</source><creator>Lustig, Michael ; Pauly, John M.</creator><creatorcontrib>Lustig, Michael ; Pauly, John M.</creatorcontrib><description>A new approach to autocalibrating, coil‐by‐coil parallel imaging reconstruction, is presented. It is a generalized reconstruction framework based on self‐consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k‐space sampling patterns. The formulation can flexibly incorporate additional image priors such as off‐resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k‐space domain are presented. These are based on a projection over convex sets and conjugate gradient algorithms. Phantom and in vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off‐resonance correction and nonlinear ℓ1‐wavelet regularization are also demonstrated. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.</description><identifier>ISSN: 0740-3194</identifier><identifier>ISSN: 1522-2594</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.22428</identifier><identifier>PMID: 20665790</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Algorithms ; autocalibration ; Calibration ; Cartesian coordinates ; compressed sensing ; Computational geometry ; Convexity ; GRAPPA ; Humans ; Image acquisition ; Image Enhancement - methods ; Image Interpretation, Computer-Assisted - methods ; Image processing ; Image reconstruction ; In vivo methods and tests ; iterative reconstruction ; Magnetic Resonance Imaging - instrumentation ; Magnetic Resonance Imaging - methods ; Optimization ; parallel imaging ; Phantoms, Imaging ; Regularization ; Reproducibility of Results ; Resonance ; SENSE ; Sensitivity and Specificity</subject><ispartof>Magnetic resonance in medicine, 2010-08, Vol.64 (2), p.457-471</ispartof><rights>Copyright © 2010 Wiley‐Liss, Inc.</rights><rights>Copyright Wiley Subscription Services, Inc. Aug 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5788-353e65dc61faa11a865e8a7938a6ea63092b9144f6ce954158ed682df3ab87663</citedby><cites>FETCH-LOGICAL-c5788-353e65dc61faa11a865e8a7938a6ea63092b9144f6ce954158ed682df3ab87663</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.22428$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.22428$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20665790$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lustig, Michael</creatorcontrib><creatorcontrib>Pauly, John M.</creatorcontrib><title>SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space</title><title>Magnetic resonance in medicine</title><addtitle>Magn. Reson. Med</addtitle><description>A new approach to autocalibrating, coil‐by‐coil parallel imaging reconstruction, is presented. It is a generalized reconstruction framework based on self‐consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k‐space sampling patterns. The formulation can flexibly incorporate additional image priors such as off‐resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k‐space domain are presented. These are based on a projection over convex sets and conjugate gradient algorithms. Phantom and in vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off‐resonance correction and nonlinear ℓ1‐wavelet regularization are also demonstrated. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.</description><subject>Algorithms</subject><subject>autocalibration</subject><subject>Calibration</subject><subject>Cartesian coordinates</subject><subject>compressed sensing</subject><subject>Computational geometry</subject><subject>Convexity</subject><subject>GRAPPA</subject><subject>Humans</subject><subject>Image acquisition</subject><subject>Image Enhancement - methods</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image processing</subject><subject>Image reconstruction</subject><subject>In vivo methods and tests</subject><subject>iterative reconstruction</subject><subject>Magnetic Resonance Imaging - instrumentation</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Optimization</subject><subject>parallel imaging</subject><subject>Phantoms, Imaging</subject><subject>Regularization</subject><subject>Reproducibility of Results</subject><subject>Resonance</subject><subject>SENSE</subject><subject>Sensitivity and Specificity</subject><issn>0740-3194</issn><issn>1522-2594</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU1rFEEQhhtRzBo9-AdkwIPkMEl_f3gQJCRxJVGJEcVLUztbs3YyM712z0T33zubTRYVxFMf6qmXp-sl5Cmj-4xSftCmdp9zye09MmGK85IrJ--TCTWSloI5uUMe5XxJKXXOyIdkh1OtlXF0Qr58_DA9Dxcvi2mPCfpwjUXGpi6r2OWQe-z6YgkJmgabIrSwCN2iSLie9mmo-hC7ok6xLSDNQp8grYqrMi-hwsfkQQ1Nxie37y75dHx0cfimPH1_Mj18fVpWylhbCiVQq3mlWQ3AGFit0IJxwoJG0II6PnNMylpX6JRkyuJcWz6vBcys0Vrskleb3OUwa3Fejcajrl-m0TatfITg_5x04ZtfxGvPHVdSqzHgxW1Ait8HzL1vQ66waaDDOGRvraCSKir_SxppneBMrqWe_0VexiF14x08l0owTd0NtbehqhRzTlhvrRn162L9WKy_KXZkn_3-zS151-QIHGyAH6HB1b-T_Nn52V1kudlY9_xzuwHpymsjjPKf3514e_xWia-WeyZ-AcGwvFU</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Lustig, Michael</creator><creator>Pauly, John M.</creator><general>Wiley Subscription Services, Inc., A Wiley Company</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>201008</creationdate><title>SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space</title><author>Lustig, Michael ; Pauly, John M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5788-353e65dc61faa11a865e8a7938a6ea63092b9144f6ce954158ed682df3ab87663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithms</topic><topic>autocalibration</topic><topic>Calibration</topic><topic>Cartesian coordinates</topic><topic>compressed sensing</topic><topic>Computational geometry</topic><topic>Convexity</topic><topic>GRAPPA</topic><topic>Humans</topic><topic>Image acquisition</topic><topic>Image Enhancement - methods</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image processing</topic><topic>Image reconstruction</topic><topic>In vivo methods and tests</topic><topic>iterative reconstruction</topic><topic>Magnetic Resonance Imaging - instrumentation</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Optimization</topic><topic>parallel imaging</topic><topic>Phantoms, Imaging</topic><topic>Regularization</topic><topic>Reproducibility of Results</topic><topic>Resonance</topic><topic>SENSE</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lustig, Michael</creatorcontrib><creatorcontrib>Pauly, John M.</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>Lustig, Michael</au><au>Pauly, John M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn. Reson. Med</addtitle><date>2010-08</date><risdate>2010</risdate><volume>64</volume><issue>2</issue><spage>457</spage><epage>471</epage><pages>457-471</pages><issn>0740-3194</issn><issn>1522-2594</issn><eissn>1522-2594</eissn><abstract>A new approach to autocalibrating, coil‐by‐coil parallel imaging reconstruction, is presented. It is a generalized reconstruction framework based on self‐consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k‐space sampling patterns. The formulation can flexibly incorporate additional image priors such as off‐resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k‐space domain are presented. These are based on a projection over convex sets and conjugate gradient algorithms. Phantom and in vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off‐resonance correction and nonlinear ℓ1‐wavelet regularization are also demonstrated. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>20665790</pmid><doi>10.1002/mrm.22428</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0740-3194 |
| ispartof | Magnetic resonance in medicine, 2010-08, Vol.64 (2), p.457-471 |
| issn | 0740-3194 1522-2594 1522-2594 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2925465 |
| source | MEDLINE; Access via Wiley Online Library; Wiley Online Library (Open Access Collection) |
| subjects | Algorithms autocalibration Calibration Cartesian coordinates compressed sensing Computational geometry Convexity GRAPPA Humans Image acquisition Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Image reconstruction In vivo methods and tests iterative reconstruction Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Optimization parallel imaging Phantoms, Imaging Regularization Reproducibility of Results Resonance SENSE Sensitivity and Specificity |
| title | SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T02%3A49%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=SPIRiT:%20Iterative%20self-consistent%20parallel%20imaging%20reconstruction%20from%20arbitrary%20k-space&rft.jtitle=Magnetic%20resonance%20in%20medicine&rft.au=Lustig,%20Michael&rft.date=2010-08&rft.volume=64&rft.issue=2&rft.spage=457&rft.epage=471&rft.pages=457-471&rft.issn=0740-3194&rft.eissn=1522-2594&rft_id=info:doi/10.1002/mrm.22428&rft_dat=%3Cproquest_pubme%3E2453160946%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2453160946&rft_id=info:pmid/20665790&rfr_iscdi=true |