StallCatchersProcessing

Original code by Mohammad Haft-Javaherian: https://github.com/mhaft/DeepVess

Some changes have been made to the post-processing in particular, taking advantage of newer MATLAB functions in the Image Processing Toolbox.

Rough steps to be followed:

1. Run PreProcessing/BatchPrepareImage.m, modifying parameters to match your system and preferences
   • Input: Stacked .tif image file
   • Output: .h5 image file
2. Run PreProcessing/createDeepVessScript.m, modifying parameters to match your system and preferences
   • Output: Stacked .bat file to be run in a command window
3. Run the above .bat file
   • Must have a functional Python virtual environment configured for DeepVess
   • See https://github.com/mhaft/DeepVess for details
   • Output: *-V_fwd.mat MATLAB data file containing the image and segmentation data
4. Run PostProcessing/BatchPostDVSkeletonize.m, modifying parameters to match your system and preferences
   • Output: Stacked Analsys-*.mat MATLAB data file containing the image, segmentation data and vessel centerlines
5. This last file can be modified/cleaned-up using the StallCatchers-Editor MATLAB app
   • https://github.com/sn-lab/StallCatchers-Editor