Segmentation of X-Ray CT Data of Porous Materials: A Review of Global and Locally Adaptive Algorithms

Recent computational and technological advances in X-ray computed tomography (CT) provide exciting new means for nondestructive, three-dimensional imaging of soil–water–root processes with projects ranging from visualization and characterization of biofilms to quantification of effects of root-induced compaction on rhizosphere hydraulic properties. In contrast to these breath-taking technological improvements, the development and evaluation of appropriate segmentation methods for transformation of three-dimensional grayscale X-ray CT data into a discrete form that allows accurate separation of solid, liquid, and vapor phases for quantitative description of the soil–water–root continuum and provides the basis for modeling of static and dynamic system processes appears to lag behind. This chapter reviews the state-of-the-art and recent developments in image segmentation, covering global and locally adaptive two-phase as well as more complex multiphase algorithms. The need for true three-dimensional segmentation is demonstrated and potential techniques for pre-segmentation enhancement of X-ray CT data are discussed.