Cone-beam CT (CBCT) images have recently become an established modality for treatment verification in radiotherapy. However, identification of soft-tissue structures and the calculation of dose distributions based on CBCT images is often obstructed by image artefacts and poor consistency of density calibration. A robust method for voxel-by-voxel enhancement of CBCT images using a priori knowledge from the planning CT scan has been developed and implemented. CBCT scans were enhanced using a low spatial frequency grey scale shading function generated with the aid of a planning CT scan from the same patient. This circumvents the need for exact correspondence between CBCT and CT and the process is robust to the appearance of unshared features such as gas pockets. Enhancement was validated using patient CBCT images. CT numbers in regions of fat and muscle tissue in the processed CBCT were both within 1% of the values in the planning CT, as opposed to 10-20% different for the original CBCT. Visual assessment of processed CBCT images showed improvement in soft-tissue visibility, although some cases of artefact introduction were observed. © 2008 Institute of Physics and Engineering in Medicine.