The g-factor is commonly used for quantifying the noise amplification associated with accelerated data acquisition and linear image reconstruction, and is frequently used to compare different k-space sampling strategies. While previous work computes g-factors in the image domain, we observe in this work that g-factors can also be used to quantify uncertainty in various transform domains (e.g., the wavelet domain and the multi-channel Fourier domain). These transform-domain g-factor maps provide complementary information to conventional image-domain g-factor maps, and are potentially useful for k-space sampling pattern design.
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