Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging

buir.contributor.authorIlicak, Efe
buir.contributor.authorSenel, Lutfi Kerem
buir.contributor.authorBiyik, Erdem
buir.contributor.authorÇukur, Tolga
dc.citation.epage1329en_US
dc.citation.issueNumber4en_US
dc.citation.spage1316en_US
dc.citation.volumeNumber78en_US
dc.contributor.authorIlicak, Efeen_US
dc.contributor.authorSenel, Lutfi Keremen_US
dc.contributor.authorBiyik, Erdemen_US
dc.contributor.authorÇukur, Tolgaen_US
dc.date.accessioned2018-04-12T10:38:46Z
dc.date.available2018-04-12T10:38:46Z
dc.date.issued2017en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentNational Magnetic Resonance Research Center (UMRAM)en_US
dc.departmentInterdisciplinary Program in Neuroscience (NEUROSCIENCE)en_US
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.description.abstractPurpose: The scan-efficiency in multiple-acquisition balanced steady-state free precession imaging can be maintained by accelerating and reconstructing each phase-cycled acquisition individually, but this strategy ignores correlated structural information among acquisitions. Here, an improved acceleration framework is proposed that jointly processes undersampled data across N phase cycles. Methods: Phase-cycled imaging is cast as a profile-encoding problem, modeling each image as an artifact-free image multiplied with a distinct balanced steady-state free precession profile. A profile-encoding reconstruction (PE-SSFP) is employed to recover missing data by enforcing joint sparsity and total-variation penalties across phase cycles. PE-SSFP is compared with individual compressed-sensing and parallel-imaging (ESPIRiT) reconstructions. Results: In the brain and the knee, PE-SSFP yields improved image quality compared to individual compressed-sensing and other tested methods particularly for higher N values. On average, PE-SSFP improves peak SNR by 3.8 ± 3.0 dB (mean ± s.e. across N = 2–8) and structural similarity by 1.4 ± 1.2% over individual compressed-sensing, and peak SNR by 5.6 ± 0.7 dB and structural similarity by 7.1 ± 0.5% over ESPIRiT. Conclusion: PE-SSFP attains improved image quality and preservation of high-spatial-frequency information at high acceleration factors, compared to conventional reconstructions. PE-SSFP is a promising technique for scan-efficient balanced steady-state free precession imaging with improved reliability against field inhomogeneity. Magn Reson Med 78:1316–1329, 2017.en_US
dc.embargo.release2018-09-20en_US
dc.identifier.doi10.1002/mrm.26507en_US
dc.identifier.issn0740-3194
dc.identifier.urihttp://hdl.handle.net/11693/36404
dc.language.isoEnglishen_US
dc.publisherJohn Wiley and Sons Inc.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1002/mrm.26507en_US
dc.source.titleMagnetic Resonance in Medicineen_US
dc.subjectBanding artifacten_US
dc.subjectCompressed sensingen_US
dc.subjectEncodingen_US
dc.subjectMagnetization profileen_US
dc.subjectReconstructionen_US
dc.subjectSSFPen_US
dc.subjectAccelerationen_US
dc.subjectArtifacten_US
dc.subjectBrainen_US
dc.subjectCase reporten_US
dc.subjectImage qualityen_US
dc.subjectImagingen_US
dc.subjectKneeen_US
dc.subjectModelen_US
dc.subjectPunishmenten_US
dc.subjectReliabilityen_US
dc.subjectSteady stateen_US
dc.titleProfile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imagingen_US
dc.typeArticleen_US

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