X-ray computed tomography (CT) is the main 3D technique for imaging the internal microstructures of materials. Quantitative analysis of the microstructures is usually achieved by applying a sequence of steps that are implemented to the entire 3D image. This is challenged by various imaging artifacts inherent from the technique, e.g., beam hardening and partial volume. Consequently, the analysis requires users to make a number of decisions to segment and classify the microstructures based on the voxel gray-values. In this context, a software tool, here called ARI3D, is proposed to interactively analyze regions in three-dimensional X-ray CT images, assisting users through the various steps of a protocol designed to classify and quantify objects within regions of a three-dimensional image. ARI3D aims to 1) Improve phase identification; 2) Account for partial volume effect; 3) Increase the detection limit and accuracy of object quantification; and 4) Harmonize quantitative 3D analysis that can be implemented in different fields of science.