Keywords: Image Reconstruction, Data Processing
Motivation: High density receive arrays can improve SNR and parallel imaging capability; however, they also introduce significant image reconstruction challenges.
Goal(s): We aim to find a reconstruction method that will produce consistent and high-quality complex images for high-channel-count receive arrays at 7T.
Approach: Several existing sensitivity map estimation methods and coil combination methods were tested for 8-channel and 32-channel datasets, and an ultrahigh resolution 96-channel dataset acquired at 7T.
Results: Existing reconstruction methods did not produce consistent results for the 96-channel dataset. Compression of high-quality sensitivity maps reduced data size by a factor of 100 while maintaining image quality.
Impact: This work explores the unique reconstruction challenges in high-channel-count receive arrays by assessing performance of existing reconstruction techniques on an ultrahigh resolution dataset acquired with a 96-channel receive array, establishing a need for more research in effective reconstruction methods.
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