Synopsis

Compressed sensing takes advantage of sparsity, incoherent sampling, and non-linear reconstruction algorithms to reduce acquisition requirements far below the Nyquist rate. This talk will provide an overview of these concepts and show how they can be used to accelerate MRI. Compressed sensing MRI examples will be discussed, including its combination with parallel imaging and application to dynamic imaging.