• DocumentCode
    1344607
  • Title

    SNR Dependence of Optimal Parameters for Apparent Diffusion Coefficient Measurements

  • Author

    Saritas, Emine U. ; Lee, Jin H. ; Nishimura, Dwight G.

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
  • Volume
    30
  • Issue
    2
  • fYear
    2011
  • Firstpage
    424
  • Lastpage
    437
  • Abstract
    Optimizing the diffusion-weighted imaging (DWI) parameters (i.e., the b-value and the number of image averages) to the tissue of interest is essential for producing high-quality apparent diffusion coefficient (ADC) maps. Previous investigation of this optimization was performed assuming Gaussian noise statistics for the ADC map, which is only valid for high signal-to-noise ratio (SNR) imaging. In this work, the true statistics of the noise in ADC maps are derived, followed by an optimization of the DWI parameters as a function of the imaging SNR. Specifically, it is demonstrated that the optimum b-value is a monotonically increasing function of the imaging SNR, which converges to the optimum b-value from previously proposed approaches for high-SNR cases, while exhibiting a significant deviation from this asymptote for low-SNR situations. Incorporating the effects of T2 weighting further increases the SNR dependence of the optimal parameters. The proposed optimization scheme is particularly important for high-resolution DWI, which intrinsically suffers from low SNR and therefore cannot afford the use of the conventional high b-values. Comparison scans were performed for high-resolution DWI of the spinal cord, demonstrating the improvements in the resulting images and the ADC maps achieved by this method.
  • Keywords
    Gaussian noise; biomedical MRI; medical image processing; neurophysiology; optimisation; Gaussian noise statistics; SNR dependence; apparent diffusion coefficient measurements; diffusion-weighted imaging parameters; high-quality apparent diffusion coefficient; optimal parameters; optimization; optimum b-value; signal-to-noise ratio imaging; spinal cord; Biomedical imaging; Estimation; Noise measurement; Optimization; Signal to noise ratio; $b$-value; Apparent diffusion coefficient; diffusion weighted imaging; optimal parameters; Algorithms; Analysis of Variance; Diffusion Magnetic Resonance Imaging; Humans; Monte Carlo Method; Phantoms, Imaging; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2010.2084583
  • Filename
    5595507