Mice are used for models of almost all human diseases and are routinely scanned by micro-CT scanners. Mouse phantoms are often used for image-quality assessment. With recent developments in deep-learning-based preclinical imaging, there is a major need for large micro-CT datasets in which ground truth is known. In this study, we investigate the feasibility of making cost-effective deformable and reconfigurable mouse phantoms to generate real micro-CT datasets that reflect realistic underlying physical characteristics. Such datasets are highly desirable; for example, complicated photon-counting micro-CT datasets are needed for deep-learning-based material decomposition. In our scheme, mouse body parts are 3Dprinted with high precision using rigid or flexible materials. Liquid tissue surrogates (LTSs) or bioinks/cell lines could be used to emulate mouse organs and physiological fluid in the animals. LTSs provide realistic x-ray properties of their biological counterparts. The LTS organs could be contained in not only 3D-printed chambers, but also dialysis tubing, which emulates the cell membrane. Furthermore, through bioprinting and tissue engineering, organs and tissues can be made even more realistic for micro-CT and other types of tomographic scanning.