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Quantitiative Diffusion Measures

Given the eigenvalues \lambda_1, \lambda_2, \lambda_3 and eigenvectors v_1, v_2, v_3 one can define many metrics.

Fractional anisotropy

Given a set of three eigenvalues \lambda_1, \lambda_2, \lambda_3  (variable ‘evalues’ in Matlab) the fractional anisotropy (FA) is calculated as:

FA = \frac{ \left(\lambda_1 - \lambda_2\right)^2+ \left( \lambda_1 - \lambda_3\right)^2 + \left( \lambda_2 - \lambda_3\right)^2}{2\left( \lambda_1^2 + \lambda_2^2 + \lambda_3^2 \right)}

which can be calculated using the following Matlab code:

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sum_sq_evalues = sum(evalues.^2);

sde = (evalues(1)-evalues(2))^2 + (evalues(2)-evalues(3))^2 + (evalues(1)-evalues(3))^2;
fa =  sqrt( sde / (2*sum_sq_evalues) );

For this, it doesn’t matter that the eigenvalues are sorted, though typically they are sorted from highest to lowest.

Apparent Diffusion Coefficient

Relative Anisotropy

Lambda Parallel

Lambda Perpendicular

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