Dual-energy ͑DE͒ imaging of the chest improves the conspicuity of subtle lung nodules through the removal of overlying anatomical noise. Recent work has shown double-shot DE imaging ͑i.e., successive acquisition of low-and high-energy projections͒ to provide detective quantum efficiency, spectral separation ͑and therefore contrast͒, and radiation dose superior to single-shot DE imaging configurations ͑e.g., with a CR cassette͒. However, the temporal separation between highenergy ͑HE͒ and low-energy ͑LE͒ image acquisition can result in motion artifacts in the DE images, reducing image quality and diminishing diagnostic performance. This has motivated the development of a deformable registration technique that aligns the HE image onto the LE image before DE decomposition. The algorithm reported here operates in multiple passes at progressively smaller scales and increasing resolution. The first pass addresses large-scale motion by means of mutual information optimization, while successive passes ͑2-4͒ correct misregistration at finer scales by means of normalized cross correlation. Evaluation of registration performance in 129 patients imaged using an experimental DE imaging prototype demonstrated a statistically significant improvement in image alignment. Specific to the cardiac region, the registration algorithm was found to outperform a simple cardiac-gating system designed to trigger both HE and LE exposures during diastole. Modulation transfer function ͑MTF͒ analysis reveals additional advantages in DE image quality in terms of noise reduction and edge enhancement. This algorithm could offer an important tool in enhancing DE image quality and potentially improving diagnostic performance.