An unbiased signal‐to‐noise ratio measure for magnetic resonance images
Copyright policy )An unbiased signal‐to‐noise ratio measure for magnetic resonance images
Estimating the true signal‐to‐noise ratio (SNR) of magnetic resonance (MR) images with low signal is confounded by the magnitude presentation of the data. This paper suggests a simple solution to this problem. A common method of measuring SNR compares the mean signal to the standard deviation of the noise. This SNR measure was found to be satisfactory for high but not low signal‐to‐noise image regions because of noise bias. These inconsistencies are removed by introducing unbiased definitions of the signal and noise levels in terms of their root‐mean‐square values. The approaches are compared by evaluating the SNR values for MR medical images.
- University of Calgary Canada
Biometry, Evaluation Studies as Topic, Biophysics, Image Processing, Computer-Assisted, Humans, Magnetic Resonance Imaging, Biophysical Phenomena
Biometry, Evaluation Studies as Topic, Biophysics, Image Processing, Computer-Assisted, Humans, Magnetic Resonance Imaging, Biophysical Phenomena
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).160 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!