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Noise propagation in region of interest measurements
Author(s) -
Hansen Michael S.,
Inati Souheil J.,
Kellman Peter
Publication year - 2015
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25194
Subject(s) - aliasing , pixel , imaging phantom , noise (video) , standard deviation , region of interest , algorithm , fourier transform , mathematics , computer science , image (mathematics) , optics , nuclear magnetic resonance , physics , artificial intelligence , mathematical analysis , statistics , undersampling
Purpose The purpose of this work was to develop and validate a technique for predicting the standard deviation (SD) associated with thermal noise propagation in region of interest measurements. Theory and Methods Standard methods for error propagation estimation were used to derive equations for the SDs of linear combinations of complex, magnitude, or phase pixel values. The equations were applied to common imaging scenarios in which the image pixels were correlated due to anisotropic pixel resolutions and parallel imaging. All SD estimates were evaluated efficiently using only vector–vector multiplications and Fourier transforms. The estimated SDs were compared to those obtained using repeated experiments and pseudo replica reconstructions. Results The proposed method was able to predict region of interest SDs in all the tested analysis scenarios. Positive and negative noise correlations caused by different parallel‐imaging aliasing point spread functions were accurately predicted, and the method predicted the confidence intervals (CI) of time‐intensity curves for in vivo cardiac perfusion measurements. Conclusion An intuitive technique for region of interest CIs was developed and validated using phantom experiments and in vivo data. Magn Reson Med 73:1300–1308, 2015. © 2014 Wiley Periodicals, Inc.