investigated lung tissue densitometry through investigating a functional relationship that calibrates the density change of the human lung tissues under quiet free breathing conditions using unique fast helical CT data and deformable image registration. Accurate accounting of dynamic lung density variation is desirable and forms the basis for treatment planning calculations. This work applied mass conservation fitting between the tissue Hounsfield units and the Jacobian values and showed that there existed differential mechanical properties of the lung tissues, allowing for their classification into three broad types, namely, parenchyma (Type I), vasculature (Type II) and soft tissues (Type III). The three types of tissues were separately modeled. The density modeling accuracy was assessed using large trials of leave-five-out cross validations, and the evaluated error was found to be comparable to the CT image noise. The proposed technique provided a valuable tool for performing human lung density analysis and will find important applications in pulmonary medical physics.