Particles on each Z-slice were localised using the MATLAB implementation of the Hough circle transform, and masks centred on the particles, whose dimensions are dependent on the particle size and imaging resolution were obtained. From these masks, key image features (the radial pixel intensity profile from the particle centre, the mask's moment of inertia, and information on the horizontal profile of the mask) were extracted. Exploratory factor analysis was then performed using the factor analyzer package to identify underlying latent numerical features, and reduce the degree of collinearity in the feature space. The labelled features extracted were then used as inputs for the model training, with a randomly shuffled train-test hold-out of 80:20 (26924 total observations, of which 21539 were used for model training). The ERT was trained on the freely available Scikit-learn package, 74 using the Scikit-learn ExtraTreesRegressor class.