Anisotropy
You can compute anisotropy for the classes within a multi-ROI using the mean intercept length (MIL) or star volume distribution (SVD) method. The options and settings for computing the degree of anisotropy are available in the Compute Measurements dialog, as shown below.
Anisotropy settings
Anisotropy is a measure of how highly oriented substructures are within a volume. For an isotropic (perfectly oriented) system, the degree of anisotropy (DA) is equal to 0. As the system becomes more anisotropic (less well-oriented), the DA increases to some value less than 1.
Mean intercept length (MIL) method… Uses the mean distance between material intersections (bone–marrow interfaces) along linear traverses over a range of orientations. Because MIL traverses cross both materials, the result is a combined measure that incorporates features of both materials. Refer to W.J. Whitehouse, The quantitative morphology of anisotropic trabecular bone, Journal of Microscopy, 101, 2, (153–168), (1974) for more information about the MIL method.
Star volume distribution (SVD) method… In this method, the distribution is determined by placing a series of points within the material of interest, and then measuring the lengths of the lines emanating from them in various directions until they encounter a boundary. These lines are considered infinitesimal cones, with their vertex at the origin and subtending a solid angle as they approach the material interface. Refer to L.M. Cruz-Orive, L.M. Karlsson, S.E. Larsen, F. Wainschtein, Characterizing anisotropy: A new concept, Micron and Microscopica Acta, 23, (75-76), (1992) for more information about the SVD method.
Refer to the table below for a description of the settings applicable to anisotropy computations.
| Description | |
|---|---|
| Sampling | Is the resolution, or distance between subsequent samples along each vector. You should note that the entered value can be equal to the voxel size of the input multi-ROI. |
| Radius | Is the radius of the sampling sphere, which determines the length of each sampling vector. |
| Tolerance | Tolerance Is the coefficient of variation. Sampling new random points will continue until either a coefficient of variation equal to the tolerance is reached or the maximum number of iterations is completed. |
| Orientations | Is the number of lines to analyze per sampling sphere. |
| Min iterations | Is the minimum number of random points in the sample that will be analyzed. |
| Max iterations | Is the maximum number of random points in the sample that will be analyzed. Fitting will stop automatically after this number is completed or if the coefficient of variation (tolerance) is reached. |
