Macro_Spatial_Dispersion

Given a set of isotropic, equidimensional binary stacks of squared images, this ImageJ macro calculates the number of
cycles of rhombicubocthedric dilation necessary to fill 90%, 95% and 99% of each volume
on the basis of the distribution of the black pixels. The macro asks for a source folder containing
a set of subfolders (mandatory) containing binary image stacks (.tif files) with equal dimensions.
The procedure is iterated over the nested folders for all the images present in every folder.
The results are saved in a target location, choosed by the operator, as a number of .txt result files
- one for each subfolder - named after the source subfolders.
Results are expressed as raw values (Hv) which are normalized, subfolder after subfolder,
according to the highest percentual volume observed in each subfolder to give nHv results. To
normalize all subfolders in a single run, the image presenting the highest percentual volume
should be present in all subfolders.

This macro has been validated against simple images manually dilated. This version analyzes all .tif stacks
present in nested folders. It behaves alike the accompanying ImageJ plugin but it is at least an order of magnitude slower. Its function was essentially that of validating the results obtained with the plugin.

本ImageJ宏脚本（ImageJ macro）基于黑色像素的空间分布，针对一组各向同性、等维的方形二进制图像堆叠，计算所需的小斜方截半立方体形态学膨胀（rhombicuboctahedric dilation）循环次数，以填充每张图像对应体积的90%、95%与99%。
该宏脚本需以一个源文件夹作为输入，该源文件夹下需包含若干子文件夹（为必填项），每个子文件夹内需存储尺寸一致的二进制图像堆叠（.tif格式文件）。将遍历所有嵌套子文件夹，对每个文件夹内的所有图像依次执行该处理流程。处理结果将保存至用户指定的目标路径，每个子文件夹对应一个.txt结果文件，文件名与对应的源子文件夹名称一致。
结果初始以原始值（Hv）的形式输出，随后将逐个子文件夹进行归一化处理：以每个子文件夹内观测到的最高体积百分比作为归一化基准，将原始值转换为归一化后的值（nHv）。若需在单次运行中完成所有子文件夹的归一化，则所有子文件夹中均需包含该具有最高体积百分比的图像。
本宏脚本已通过手动进行形态学膨胀的简单图像完成验证。当前版本可分析嵌套文件夹内的所有.tif图像堆叠，其功能与配套的ImageJ插件一致，但运行速度至少比插件慢一个数量级，核心作用为验证插件所得到的计算结果。