Three‐dimensional reconstruction of porous polymer films from FIB‐SEM nanotomography data using random forests

Dataset and code used in M. Röding, et al, "Three-dimensional reconstruction of porous polymer films from FIB-SEM nanotomography data using random forests", published in Journal of Microscopy, 2020. In this work, we develop a segmentation method for focused ion beam scanning electron microscopy (FIB-SEM) data acquired by volumetric imaging of porous polymer films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. This type of polymer films are used for controlled release applications. Based on manual segmentation of a fraction of the data, a random forest classifier is trained and applied to the full data set. Here, raw data, manual segmentations, and the Matlab code used for all steps in the analysis are supplied.