Characterizing, measuring, and utilizing the resolution of CT imagery for improved quantification of fine-scale features

Quantitative results extracted from computed tomographic (CT) data sets should be the same across resolutions and between different instruments and laboratory groups. Despite the proliferation of scanners and data processing methods and tools, and scientific studies utilizing them, relatively little emphasis has been given to ensuring that these results are comparable or reproducible. This issue is particularly pertinent when the features being imaged and measured are of the same order size as data voxels, as is often the case with fracture apertures, pore throats, and cell walls. We have created a tool that facilitates quantification of the spatial resolution of CT data via its point-spread function (PSF), in which the user draws a traverse across a sharp interface between two materials and a Gaussian PSF is fitted to the blurring across that interface. Geometric corrections account for voxel shape and the angle of the traverse to the interface, which does not need to be orthogonal. We use the tool to investigate a series of grid phantoms scanned at varying conditions and observe how the PSF varies within and between slices. The PSF increases with increasing radial distance within slices, and can increase tangentially with increasing radial distance in CT data sets acquired with relatively few projections. The PSF between CT slices is similar to that within slices when a 2-D detector is used, but is much sharper when the data are acquired one slice at a time with a collimated linear detector array. The capability described here can be used not only to calibrate processing algorithms that use deconvolution operations, but it can also help evaluate scans on a routine basis within and between CT research groups, and with respect to the features within the imagery that are being measured.