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Abstract #3660

Joint Image Reconstruction and Sensitivity Estimation in SENSE (JSENSE)

Ying L, Liu B, Sheng J
University of Wisconsin

Parallel imaging has emerged as an effective tool to reduce imaging time in various dynamic imaging applications. This paper considers the inaccuracy of coil sensitivity estimation in conventional reconstruction methods such as SENSE, and reformulates the image reconstruction problem as a joint estimation of the coil sensitivities and the desired image, which is solved by an iterative algorithm (JSENSE). Simulation based on an eight-channel configuration demonstrates that the proposed method effectively corrects the sensitivity errors and thereby improves reconstruction especially when large acceleration factors are used.