X-ray microscopy (XRM) and light-sheet fluorescence microscopy (LSFM) have emerged as pivotal tools in preclinical research, particularly for studying bone remodeling diseases such as osteoporosis. To enable micrometer-level structural correspondence and facilitate functional analysis, we introduce BigReg, an automatic, two-stage registration pipeline optimized for high-resolution XRM and LSFM volumes [1]. The first stage involves extracting surface features and applying two successive global-to-local point cloud-based methods for coarse alignment. The subsequent stage refines this alignment in the 3D Fourier domain using a modified cross-correlation technique, achieving precise volumetric registration. Evaluations using expert-annotated landmarks and augmented test data demonstrate that BigReg approaches the accuracy of landmark-based registration with a landmark distance (LMD) of 8.36 μm ± 0.12 μm and a landmark fitness (LM fitness) of 85.71% ± 1.02%. Moreover, BigReg can provide an optimal initialization for mutual information-based methods which otherwise fail independently, further reducing LMD to 7.24 μm ± 0.11 μm and increasing LM fitness to 93.90% ± 0.77%. To the best of our knowledge, BigReg is the first automated method to successfully register XRM and LSFM volumes without requiring manual intervention or prior alignment cues, thus opening up newavenues for multimodal analysis of bone microarchitecture and disease pathology.