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Quantification of hepatic steatosis using magnetic resonance imaging

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Academic year: 2020

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Table 3.5 and Figure 3.6 show the estimated x for the acquired z, actual percentage and abso- abso-lute error for FA in each phantom for the tight constraint
Figure 3.8 shows the relation between the Gaussian noise added to the simulated MR spectrum (~ z) and the L2 norm of the error between the simulated and the actual values of ~ x from Table 3.3.
Table 3.6 and Figure 3.10 show the sensitivity and specificity of the proposed methodology for differentiating normal from diseased liver, and between steatosis without (ST) and with (SH) inflammation according with the level of added Gaussian noise (np) a
Table 4.3 shows the final ~ z value normalized for each oil and water sample. Figure 4.1 shows the simulated image phantom obtained applying the inverse Fast Fourier transform in 2D, and the field variation applied

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