To advance our understanding of carious process and our ability to create effective caries treatments, cariologists need to mine, visualize, and analyze large dental imaging data. Cariologists often base their reporting on checking a large number of images, structuring and bringing all the needed information to them have become highly challenging. In this paper, we introduce a family of visual computing technologies for us to intuitively explore dental imaging data. We exploit image analysis, volumetric construction, and geometric analysis methods in particular to quantitatively assess dynamic carious lesion activities. In this way, cariologists can proceed to study families of dental domain-specific problems such as quantitative assessment of dynamic carious lesion activities and accurate measurement of the distance between the lesion and dental pulp in vivo.