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Abstract #4582

Recoverability Bounds for Parallel Compressive Sensing MRI

Joshua D. Trzasko1, Armando Manduca1

1Center for Advanced Imaging Research, Mayo Clinic, Rochester, MN, USA


Compressive Sensing (CS) and parallel imaging are two distinct techniques in MR imaging that allow for accelerated acquisition while retaining image quality. Recent advances have shown that these two methods may be naturally combined to provide even taster exams. In this work, we investigate the theoretical signal recovery properties of the hybrid model and derive a relationship between recoverability, the sampling model, and coil sensitivity profiles.

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