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Abstract #2674

An Eigen-Vector Approach for Coil Sensitivity Estimation in the 3D Scenario

Qiu Wang1, Jun Liu1, Michael O. Zenge2, Nirmal Janardhanan1, Edgar Mueller2, Mariappan S. Nadar1

1Imaging and Computer Vision, Siemens Corporation, Corporate Technology, Princeton, NJ, United States; 2MR Application & Workflow Development, Siemens AG, Healthcare Sector, Erlangen, Bavaria, Germany

Parallel imaging achieves scan time reduction by utilizing the correlation among an array of receiver coils to reconstruct image from under-sampled data. For SENSE-type reconstruction, explicit estimation of the coil sensitivity map (CSM) is critical in achieving good image quality. When the data is acquired using 3D Cartesian sampling, one way for estimating the coil profiles is to decouple the data along the frequency encoding direction and then perform the estimation in a 2D manner, which, however, ignores the correlation between the calibration data in the frequency encoding direction. In this work, we propose a 3D CSM estimation method, extending the Eigen-Vector approach that was developed for the 2D scenario. Experiments show the coil profiles are smoother with proposed approach compared to the 2D estimation method, and good image quality has been achieved.