File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: PEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction

TitlePEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction
Authors
KeywordsSMS
multiband
Nyquist ghost
parallel imaging
GRAPPA
EPI
Issue Date2019
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0740-3194/
Citation
Magnetic Resonance in Medicine, 2018, v. 81 n. 3, p. 1924-1934 How to Cite?
Abstract© 2018 International Society for Magnetic Resonance in Medicine Purpose: To provide simultaneous multislice (SMS) EPI reconstruction with k-space implementation and robust Nyquist ghost correction. Methods: 2D phase error correction SENSE (PEC-SENSE) was recently developed for Nyquist ghost correction in SMS EPI reconstruction for which virtual coil simultaneous autocalibration and k-space estimation (VC-SAKE) was used to remove slice-dependent Nyquist ghosts and intershot 2D phase variations in multi-shot EPI reference scan. However, masking coil sensitivity maps to exclude background region in PEC-SENSE and manually selecting slice-wise target ranks in VC-SAKE are cumbersome procedures in practice. To avoid masking, the concept of PEC-SENSE is extended to k-space implementation and termed as PEC-GRAPPA. Furthermore, a singular value shrinkage scheme is incorporated in VC-SAKE to circumvent the empirical slice-wise target rank selection. PEC-GRAPPA was evaluated and compared to PEC-SENSE with/without masking and 1D linear phase correction GRAPPA. Results: PEC-GRAPPA robustly reconstructed SMS EPI images from 7T phantom and human brain data, effectively removing the phase error-induced artifacts. The resulting residual artifact level and temporal SNR were comparable to those by PEC-SENSE with careful tuning. PEC-GRAPPA outperformed PEC-SENSE without masking and 1D linear phase correction GRAPPA. Conclusion: Our proposed PEC-GRAPPA approach effectively removes the artifacts caused by Nyquist ghosts in SMS EPI without cumbersome tuning. This approach provides a robust and practical implementation of SMS EPI reconstruction in k-space with slice-dependent 2D Nyquist ghost correction.
DescriptionThis study was first presented at the 2018 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), Paris, June 18–22, 2018
Persistent Identifierhttp://hdl.handle.net/10722/265795
ISSN
2021 Impact Factor: 3.737
2020 SCImago Journal Rankings: 1.696
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Yilong-
dc.contributor.authorLyu, Mengye-
dc.contributor.authorBarth, Markus-
dc.contributor.authorYi, Zheyuan-
dc.contributor.authorLeong, Alex T.L.-
dc.contributor.authorChen, Fei-
dc.contributor.authorFeng, Yanqiu-
dc.contributor.authorWu, Ed X.-
dc.date.accessioned2018-12-03T01:21:43Z-
dc.date.available2018-12-03T01:21:43Z-
dc.date.issued2019-
dc.identifier.citationMagnetic Resonance in Medicine, 2018, v. 81 n. 3, p. 1924-1934-
dc.identifier.issn0740-3194-
dc.identifier.urihttp://hdl.handle.net/10722/265795-
dc.descriptionThis study was first presented at the 2018 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), Paris, June 18–22, 2018-
dc.description.abstract© 2018 International Society for Magnetic Resonance in Medicine Purpose: To provide simultaneous multislice (SMS) EPI reconstruction with k-space implementation and robust Nyquist ghost correction. Methods: 2D phase error correction SENSE (PEC-SENSE) was recently developed for Nyquist ghost correction in SMS EPI reconstruction for which virtual coil simultaneous autocalibration and k-space estimation (VC-SAKE) was used to remove slice-dependent Nyquist ghosts and intershot 2D phase variations in multi-shot EPI reference scan. However, masking coil sensitivity maps to exclude background region in PEC-SENSE and manually selecting slice-wise target ranks in VC-SAKE are cumbersome procedures in practice. To avoid masking, the concept of PEC-SENSE is extended to k-space implementation and termed as PEC-GRAPPA. Furthermore, a singular value shrinkage scheme is incorporated in VC-SAKE to circumvent the empirical slice-wise target rank selection. PEC-GRAPPA was evaluated and compared to PEC-SENSE with/without masking and 1D linear phase correction GRAPPA. Results: PEC-GRAPPA robustly reconstructed SMS EPI images from 7T phantom and human brain data, effectively removing the phase error-induced artifacts. The resulting residual artifact level and temporal SNR were comparable to those by PEC-SENSE with careful tuning. PEC-GRAPPA outperformed PEC-SENSE without masking and 1D linear phase correction GRAPPA. Conclusion: Our proposed PEC-GRAPPA approach effectively removes the artifacts caused by Nyquist ghosts in SMS EPI without cumbersome tuning. This approach provides a robust and practical implementation of SMS EPI reconstruction in k-space with slice-dependent 2D Nyquist ghost correction.-
dc.languageeng-
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0740-3194/-
dc.relation.ispartofMagnetic Resonance in Medicine-
dc.subjectSMS-
dc.subjectmultiband-
dc.subjectNyquist ghost-
dc.subjectparallel imaging-
dc.subjectGRAPPA-
dc.subjectEPI-
dc.titlePEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction-
dc.typeArticle-
dc.identifier.emailLiu, Y: loyalliu@hku.hk-
dc.identifier.emailLeong, TL: tlleong@hku.hk-
dc.identifier.emailWu, EX: ewu@eee.hku.hk-
dc.identifier.authorityLeong, TL=rp02483-
dc.identifier.authorityWu, EX=rp00193-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/mrm.27546-
dc.identifier.scopuseid_2-s2.0-85055942876-
dc.identifier.hkuros304418-
dc.identifier.volume81-
dc.identifier.issue3-
dc.identifier.spage1924-
dc.identifier.epage1934-
dc.identifier.eissn1522-2594-
dc.identifier.isiWOS:000462091200037-
dc.publisher.placeUnited States-
dc.identifier.issnl0740-3194-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats