Cone beam computed tomography systems generate 3D volumetric images, which provide further morphological
information compared to radiography and tomosynthesis systems. However, reconstructed images by FDK algorithm
contain cone beam artifacts when a cone angle is large. To reduce the cone beam artifacts, two-pass algorithm has been
proposed. The two-pass algorithm considers the cone beam artifacts are mainly caused by high density materials, and
proposes an effective method to estimate error images (i.e., cone beam artifacts images) by the high density materials.
While this approach is simple and effective with a small cone angle (i.e., 5 - 7 degree), the correction performance is
degraded as the cone angle increases. In this work, we propose a new method to reduce the cone beam artifacts using a
dual energy technique. The basic idea of the proposed method is to estimate the error images generated by the high
density materials more reliably. To do this, projection data of the high density materials are extracted from dual energy
CT projection data using a material decomposition technique, and then reconstructed by iterative reconstruction using
total-variation regularization. The reconstructed high density materials are used to estimate the error images from the
original FDK images. The performance of the proposed method is compared with the two-pass algorithm using root
mean square errors. The results show that the proposed method reduces the cone beam artifacts more effectively,
especially with a large cone angle.