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Abstract #2405

Self-Estimated Subspace Reconstruction for Highly-Accelerated Dynamic Golden-Angle Radial MRI

Li Feng1, Qiuting Wen2, Hersh Chandarana3, and Ricardo Otazo1,4

1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Department of Radiology, Indiana University School of Medicine, Indianapolis, IN, United States, 3Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, United States, 4Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States

Subspace-constrained reconstruction is a powerful technique to accelerate dynamic MRI. However, its performance is relatively limited for applications where a robust temporal model is not available. This work proposes to estimate temporal basis from undersampled dynamic golden-angle radial data without the need of a model or additional navigators, and to apply the estimated temporal basis for subspace-constrained reconstruction of undersampled dynamic images. The reconstruction algorithm also enforces an additional low-rank constraint on the resulting low dimensional dynamic images in the subspace. The proposed self-estimated subspace-constrained reconstruction technique was demonstrated for DCE-MRI of the prostate.

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