Piecewise linear fitting in dynamic micro-CT

Abstract Piecewise linear fitting, the technique proposed in this paper, performs data reduction on a large dynamic CT dataset and it already takes a step in the direction of the data analysis and characterization that needs to be performed afterwards. In addition, it drastically improves the signal-to-noise ratio. This is demonstrated on two complementary samples: a Bentheimer sandstone and a pharmaceutical tablet. This technique is developed for dynamic high-resolution CT scanning or 4D-μCT, a tool to study dynamic processes in situ on the micro-scale. We propose to start from the low quality reconstruction and perform a piecewise linear fit in the time direction for each voxel. This effectively uses the nearby temporal information, regardless of the nature of the dynamic process, without introducing spatial correlation.

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