Topological frameworks like discrete Morse theory and persistent homology enable practical tools for the study and analysis of scientific data due to their ability to robustly extract shape and structure even in the presence of noise. MorseGram is a software tool for segmenting 3D Xray CT scanned granular materials using a Morse theory-based algorithm. It also supports a data structure that efficiently stores both the segmentation and the connectivity network representing the inter-particle arrangement. Salient features of the method, such as the locally-optimal boundary extraction, an efficient and flexible framework for noise removal and a geometry-aware connectivity network, ensure that the approach generalizes to diverse packing structures with variation in particle size, geometry, and material density.

Source code and instructions available in the bitbucket repository.

References

1. Karran Pandey, Talha Bin Masood, Saurabh Singh, Ingrid Hotz, Vijay Natarajan, and Tejas G. Murthy.
   Morse theory-based segmentation and fabric quantification of granular materials
   Granular Matter, 24(1), 2022, 27:1-20.
   [Springer link]