![]() ![]() This Anisotropy is not repeated until results stabilise like in BoneJ1.The measures are reported separately for each 3D subspace in the image, i.e. It is a numerical list of the values displayed in 3D in the MIL point cloud. MIL vectors (optional): the ( x, y, z) coordinates of the mean intercept length at each probe orientation are printed to a new result table.This will give a visualisation of the MIL cloud aligned to the imput data. number of directions to draw probes nDirsMax = 32768 // From Image, but note you first have to decalibrate the input image (Image > Properties…, set all Pixel width, height & depth to 1 pixel). We recommend running the following macro on a typical image from your experiments. ![]() It is helpful to run a convergence analysis to determine settings that lead to a stable result in a reasonable amount of time. Print MIL vectors if checked, prints the ( x, y, z) MIL vector coordinates to a result table.Display MIL vectors if checked, shows the MIL vectors plotted in a point cloud on 3D Viewer.Show Eigens if checked, then the eigenvectors and values of the fitted ellipsoid are shown in the results table.Show radii: if checked, then the radii of the fitted ellipsoid are shown in the results table.However, these minimums are not guaranteed to be the best settings for your image. In our tests we found that with these values the results are quite stable, and fitting unlikely to fail. Recommended minimum: if checked, then the above three parameters are set to the recommended minimum values.The number of samples taken per line depends on the length of the line segment within the image stack. In the first step the algorithm draws parallel lines over the input image in direction \(\mathbf\). Thus it’s recommended to run it several times to establish the degree of anisotropy in your image. It’s important to note that algorithm is stochastic and does not guarantee exact results. ![]()
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