Research data supporting 'MicroCT analysis of connectivity in porous structures: optimising data acquisition and analytical methods in the context of tissue-engineering'

Research data supporting 'MicroCT analysis of connectivity in porous structures: optimising data acquisition and analytical methods in the context of tissue-engineering'. This data-set contains the methods (in .py files) and raw structural data (in .xlsx format) of two distinct data-sets investigated in the main manuscript: #1 percanalyser.py contains the code to run the segmented percolation algorithm and output the required data for further analysis. The structural data (including pore size, pore size distribution as obtained from CTAnalyser's 3D Object analysis tool and raw interconnectivity data as calculated from CTAnalyser's shrink wrap and 3D Object analysis tool), as well as the results from the percolation analysis are provided in #2 ArtficialDataAnalysis.xlsx for the artificially generated data and #3 ScaffoldDataAnalysis.xlsx for the structurally graduated scaffolds. Data are labelled according to the passes of noise (0, 1, 2, 4, 8), varying alignments of meshes (0 for a 'Shifted' and 1 for an 'Aligned' lattice) for the artificial meshes and as 'Top' or 'Bottom' for the dual-layered scaffolds. #4 postanalysis.py includes methods uses to extract percolation diameters and interconnection diameters from the raw data files as obtained from the percanalyser.py (#1) script and CTAnalyser programs. Please see the main manuscript for further details.