Breaking the noise floor: A framework for correcting the noise-induced bias in noisy magnitude MR signals

Breaking the noise floor: A framework for correcting the noise-induced bias in noisy magnitude MR signals Cheng Guan Koay, Evren Özarslan, Peter J. Basser STBB / NICHD, National Institutes of Health, Bethesda, MD, United States MR signals are complex numbers where the real and imaginary components are independently Gaussian distributed [1]. The phase of the complex MRI signal is highly sensitive to many experimental factors, e.g., see [1,2], and as such, the magnitude of the complex MR signal (hereafter, magnitude MR signal) is used instead. However, the magnitude MR signal is not an optimal estimate of the underlying signal intensity when the signal-to-noise ratio is low because magnitude MR signals follow a Rician distribution rather than a Gaussian distribution [3]. Here, we present a scheme to remove the noise-induced bias in noisy magnitude MR signals by making noisy Rician signals Gaussian-distributed.