Purpose: Dual-energy cone-beam CT (DE-CBCT) is an emerging technology with potential application in diagnostic imaging and image-guided interventions. This paper reports DE-CBCT feasibility and investigates decomposition algorithms for maximizing low-dose performance for reconstruction-based DE decomposition. A framework of binary decision theory is used to examine the accuracy of DE decompositions obtained from analytical reconstructions of differentially filtered low-energy (LE) and high-energy (HE) data and from penalized likelihood (PL) reconstructions with differential regularization using quadratic and total variation penalties. Methods: Accurate DE-CBCT decomposition benefits from consideration of all system noise components. Filtered backprojection (FBP) reconstruction-based decomposition was investigated with differential filtering of LE and HE data. Penalized likelihood reconstruction-based decomposition with differential regularization was hypothesized to further improve low-dose performance, especially when coupled with regularization through a total variation edge preserving penalty that encourages piecewise smooth images. Performance of decomposition was assessed in terms of a binary hypothesis framework of sensitivity, specificity, and accuracy. Studies involved experiments on a DE-CBCT testbench, phantoms of variable material type and concentration, and cadavers (knee arthrography). Results: Studies support the overall feasibility of accurate, low-dose DE-CBCT at concentration down to 5 mg/ml (iodine), dose ∼3-6 mGy, and accuracy of material classification ~90%. Reconstruction-based decomposition with quadratic PL performed comparably to FBP. PL with a total variation penalty provided edge preservation and piecewise smooth images that aided DE classification and achieved improved performance over FBP and quadratic PL, reaching accuracy of ∼ 0.98 for 2 mg/mL iodine at 3.2 mGy, compared to approx. 0.9 for FBP and quadratic PL. Conclusions: Accurate material decomposition with DE-CBCT is feasible at low dose and benefits from a rigorous assessment of noise mechanisms among various reconstruction-based techniques. The work points to the potential for non-linear iterative reconstruction methods for high-quality decomposition at low material concentration and dose.