The code was developed for and is described in the paper Rose et al, MRM, 2019. Please cite it if you find it useful.
All files for the example are located in the example directory.
The segmentation can be done using masks, e.g. using GIMP. It then needs to be exported as a TIF image, with at least the following 3 pages:
- Raw histology image
- Segmentation image
- Group image
In GIMP, to apply the colour from the group layer to the black-white segmentation, see here.
It also needs metadata about the image resolution. This can be added like this:
exiftool -XResolution=2 -YResolution=2 <image_file>
Due to an apparent bug in Windows 10, layered TIF images can crash Windows Explorer and make deleting/renaming/moving the file impossible. Therefore, the file is saved as example.tif_layered which can still be read by MATLAB but does not affect Windows.
The example image is obtained in MATLAB via imread('coins.png'), segmented as done in the "Fill Holes in a Binary Image" example, and the groups manually (arbitrarily) segmented in GIMP.
To execute example.mlx, the source directory ./src/ needs to be on the MATLAB path.
The paths in example.mlx assume you are in the same working directory as the script itself.