Review of porosity uncertainty estimation methods in computed tomography dataset

Abstract

Abstract X-ray computed tomography is a common tool for non-destructive testing and analysis. One major application of this imaging technique is 3D porosity identification and quantification, which involves image segmentation of the analysed dataset. This segmentation step, which is most commonly performed using a global thresholding algorithm, has a major impact on the results of the analysis. Therefore, a thorough description of the workflow and a general uncertainty estimation should be provided alongside the results of porosity analysis to ensure a certain level of confidence and reproducibility. A review of current literature in the field shows that a sufficient workflow description and an uncertainty estimation of the result are often missing. This work provides recommendations on how to report the processing steps for porosity evaluation in computed tomography data using global thresholding, and reviews the methods for the estimation of the general uncertainty in porosity measurements.