University of Heidelberg
Faculty of Medicine Mannheim
University Hospital Mannheim
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Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging

E. Ilicak, L. Senel, E. Biyik and T. Çukur

Magn Reson Med, 78, pp.1316-1329

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. 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. 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. 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. © 2016 International Society for Magnetic Resonance in Medicine.

Contact: Dr. Frank Zöllner last modified: 30.11.2020
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