The application results of a hybrid machine learning approach for segmentation of methane hydrate-bearing sample.

This rar archive contains the result of applying the hybrid machine learning segmentation algorithm to the reconstructed CT volume obtained during the formation of methane hydrate in a sand sample. Archive content: raw_volume.tiff - CT volume acquired during a dynamic in-situ experiment at the bending magnet beamline 2-BM of the Advanced Photon Source, Argonne National Laboratory. segmented_volume.tiff - segmented CT volume with following phases: 0 - background, 1 - sand grains, 2 - methane gas, 3 - methane gas hydrate, 4 - mixture of hydrate and brine, 5 - NaBr brine. This data is refrenced in our companion paper "Enabling quantitative analysis of time-resolved CT imaging of methane-hydrate formation with a hybrid machine learning approach"