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Abstract #4862

Autocalibrated Approach for the Combination of Compressed Sensing and SENSE

Claudia Prieto1, Benjamin R. Knowles1, Muhammad Usman1, Philip G. Batchelor1, Freddy Odille2, David Atkinson2, Tobias Schaeffter1

1Division of Imaging Sciences, King's College London, London, United Kingdom; 2Centre for Medical Image Computing, University College London, London, United Kingdom

An autocalibrated approach for the combination of Compressed Sensing (CS) and SENSE is proposed. This method is based on the sequential estimation of the coil sensitivity maps using distributed CS followed by image reconstruction using SparseSENSE (or its equivalents), from the same data set. The proposed approach was tested in 2D black-blood atrial wall images with undersampling factors up to 5, showing good image quality. This method does not require extra reference scans and avoids the acquisition of the fully sampled k-space center, which could limit the maximum achievable undersampling factor.