Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging
buir.contributor.author | Ilicak, Efe | |
buir.contributor.author | Senel, Lutfi Kerem | |
buir.contributor.author | Biyik, Erdem | |
buir.contributor.author | Çukur, Tolga | |
dc.citation.epage | 1329 | en_US |
dc.citation.issueNumber | 4 | en_US |
dc.citation.spage | 1316 | en_US |
dc.citation.volumeNumber | 78 | en_US |
dc.contributor.author | Ilicak, Efe | en_US |
dc.contributor.author | Senel, Lutfi Kerem | en_US |
dc.contributor.author | Biyik, Erdem | en_US |
dc.contributor.author | Çukur, Tolga | en_US |
dc.date.accessioned | 2018-04-12T10:38:46Z | |
dc.date.available | 2018-04-12T10:38:46Z | |
dc.date.issued | 2017 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.department | National Magnetic Resonance Research Center (UMRAM) | en_US |
dc.department | Interdisciplinary Program in Neuroscience (NEUROSCIENCE) | en_US |
dc.department | Aysel Sabuncu Brain Research Center (BAM) | en_US |
dc.description.abstract | Purpose: 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.release | 2018-09-20 | en_US |
dc.identifier.doi | 10.1002/mrm.26507 | en_US |
dc.identifier.issn | 0740-3194 | |
dc.identifier.uri | http://hdl.handle.net/11693/36404 | |
dc.language.iso | English | en_US |
dc.publisher | John Wiley and Sons Inc. | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1002/mrm.26507 | en_US |
dc.source.title | Magnetic Resonance in Medicine | en_US |
dc.subject | Banding artifact | en_US |
dc.subject | Compressed sensing | en_US |
dc.subject | Encoding | en_US |
dc.subject | Magnetization profile | en_US |
dc.subject | Reconstruction | en_US |
dc.subject | SSFP | en_US |
dc.subject | Acceleration | en_US |
dc.subject | Artifact | en_US |
dc.subject | Brain | en_US |
dc.subject | Case report | en_US |
dc.subject | Image quality | en_US |
dc.subject | Imaging | en_US |
dc.subject | Knee | en_US |
dc.subject | Model | en_US |
dc.subject | Punishment | en_US |
dc.subject | Reliability | en_US |
dc.subject | Steady state | en_US |
dc.title | Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging | en_US |
dc.type | Article | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Profile‐encoding reconstruction for multiple‐acquisition balanced steady‐state free precession imaging.pdf
- Size:
- 6.13 MB
- Format:
- Adobe Portable Document Format
- Description:
- Full printable version