On the noise in "augmented T1-weighted steady state magnetic resonance imaging".
Jochen LeupoldValerij G KiselevPublished in: NMR in biomedicine (2022)
Recently, Ye and colleagues proposed a method for "augmented T1-weighted imaging" (aT 1 W). The key operation is a complex division of gradient-echo (GRE) images obtained with different flip angles. Ye and colleagues provide an equation for the standard deviation of the obtained aT 1 W signal. Here, we show that this equation leads to wrong values of the standard deviation of such an aT 1 W signal. This is demonstrated by Monte Carlo simulations. The derivation of the equation provided by Ye and colleagues is shown to be erroneous. The error consists of a wrong handling of random variables and their standard deviations and of the wrong assumption of correlated noise in independently acquired GRE images. Instead, the probability distribution obtained with the aT 1 W-method should have been carefully analyzed, perhaps on the basis of previous literature on ratio distributions and their normal approximations.
Keyphrases
- monte carlo
- contrast enhanced
- magnetic resonance imaging
- magnetic resonance
- deep learning
- convolutional neural network
- air pollution
- optical coherence tomography
- diffusion weighted
- systematic review
- high resolution
- computed tomography
- network analysis
- diffusion weighted imaging
- molecular dynamics
- machine learning
- fluorescence imaging