Spatially varying noise limits acquisition speed and spatial resolution in multi-channel MRI. Conventional single-slice noise-suppressing image filters without additional knowledge about data acquisition, image reconstruction, and noise level, have limited performance and need parameter tuning. In this work, an iterative denoising algorithm is presented which works with standard settings on 3D complex-valued data with supplementary information from the scanner environment.
Initial results from routine clinical imaging are promising: spatially adaptive, as intended, and superior to a commercially available image filter. Non-optimized reconstruction times of up to 15min per volume still need improvement, and further clinical investigations will be performed.
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