BUDA-MESMERISE: Rapid acquisition and unsupervised parameter estimation for T-1, T-2, M-0, B-0, and B-1 maps

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dc.contributor.authorSo, Seoheeko
dc.contributor.authorPark, Hyun Wookko
dc.contributor.authorKim, Byungjaiko
dc.contributor.authorFritz, Francisco J.ko
dc.contributor.authorPoser, Benedikt A.ko
dc.contributor.authorRoebroeck, Alardko
dc.contributor.authorBilgic, Berkinko
dc.date.accessioned2022-05-06T08:00:13Z-
dc.date.available2022-05-06T08:00:13Z-
dc.date.created2022-04-11-
dc.date.issued2022-07-
dc.identifier.citationMAGNETIC RESONANCE IN MEDICINE, v.88, no.1, pp.292 - 308-
dc.identifier.issn0740-3194-
dc.identifier.urihttp://hdl.handle.net/10203/296402-
dc.description.abstractPurpose Rapid acquisition scheme and parameter estimation method are proposed to acquire distortion-free spin- and stimulated-echo signals and combine the signals with a physics-driven unsupervised network to estimate T-1, T-2, and proton density (M-0) parameter maps, along with B-0 and B-1 information from the acquired signals. Theory and Methods An imaging sequence with three 90 degrees RF pulses is utilized to acquire spin- and stimulated-echo signals. We utilize blip-up/-down acquisition to eliminate geometric distortion incurred by the effects of B-0 inhomogeneity on rapid EPI acquisitions. For multislice imaging, echo-shifting is applied to utilize dead time between the second and third RF pulses to encode information from additional slice positions. To estimate parameter maps from the spin- and stimulated-echo signals with high fidelity, 2 estimation methods, analytic fitting and a novel unsupervised deep neural network method, are developed. Results The proposed acquisition provided distortion-free T-1, T-2, relative proton density (M0), B-0, and B-1 maps with high fidelity both in phantom and in vivo brain experiments. From the rapidly acquired spin- and stimulated-echo signals, analytic fitting and the network-based method were able to estimate T-1, T-2, M-0, B-0, and B-1 maps with high accuracy. Network estimates demonstrated noise robustness owing to the fact that the convolutional layers take information into account from spatially adjacent voxels. Conclusion The proposed acquisition/reconstruction technique enabled whole-brain acquisition of coregistered, distortion-free, T-1, T-2, M-0, B-0, and B-1 maps at 1 x 1 x 5 mm(3) resolution in 50 s. The proposed unsupervised neural network provided noise-robust parameter estimates from this rapid acquisition.-
dc.languageEnglish-
dc.publisherWILEY-
dc.titleBUDA-MESMERISE: Rapid acquisition and unsupervised parameter estimation for T-1, T-2, M-0, B-0, and B-1 maps-
dc.typeArticle-
dc.identifier.wosid000773656700001-
dc.identifier.scopusid2-s2.0-85127243910-
dc.type.rimsART-
dc.citation.volume88-
dc.citation.issue1-
dc.citation.beginningpage292-
dc.citation.endingpage308-
dc.citation.publicationnameMAGNETIC RESONANCE IN MEDICINE-
dc.identifier.doi10.1002/mrm.29228-
dc.contributor.localauthorPark, Hyun Wook-
dc.contributor.nonIdAuthorFritz, Francisco J.-
dc.contributor.nonIdAuthorPoser, Benedikt A.-
dc.contributor.nonIdAuthorRoebroeck, Alard-
dc.contributor.nonIdAuthorBilgic, Berkin-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthordistortion correction-
dc.subject.keywordAuthormulticontrast MRI-
dc.subject.keywordAuthorquantitative MRI-
dc.subject.keywordAuthorstimulated echo-
dc.subject.keywordAuthorunsupervised parameter estimation-
dc.subject.keywordPlusPROTON DENSITY-
dc.subject.keywordPlusTISSUE CHARACTERIZATION-
dc.subject.keywordPlusINCREASED SENSITIVITY-
dc.subject.keywordPlusQUANTITATIVE MRI-
dc.subject.keywordPlusWHITE-MATTER-
dc.subject.keywordPlusDOUBLE-ECHO-
dc.subject.keywordPlusT2-
dc.subject.keywordPlusT1-
dc.subject.keywordPlusDIFFUSION-
dc.subject.keywordPlusBRAIN-
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EE-Journal Papers(저널논문)
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