Carlos Fernndez-Granda1,2, Julien Sngas3
1cole des Mines, Paris, France; 2Universidad Politcnica de Madrid, Spain; 3Philips Research Europe, Hamburg, Germany
Joint estimation of the coil sensitivities and the image in parallel imaging can suppress aliasing more effectively than methods based on low-resolution sensitivity estimates. We propose a joint estimation approach related to Compressed Sensing that exploits the sparsity of the coil sensitivities in k-space and in a base of Chebyshev polynomials within a greedy scheme to solve the ill-posed reconstruction problem. In vivo data reconstructions are presented and compared to results obtained with Generalized SENSE and Joint SENSE.