Diagnostic and surgical strategies could benefit from accurate localization of liver malignancies via CT-FDG-PET image registration. However, registration uncertainty occurs due to protocol differences in data-acquisition, the limited spatial resolution of positron emission tomography (PET) and the low uptake of 18F-fluorodeoxyglucose (FDG) in normal liver tissue. To assess this uncertainty, methods were presented to estimate registration precision and systematic bias. A semi-automatic, organ-focused method was investigated to minimize the uncertainty well beyond the typical uncertainty of 5-10 mm obtained by commonly available methods. By restricting registration to the liver region and by isolating the liver on computed tomography (CT) from surrounding structures using a thresholding technique, registration was achieved using the mutual information-based method as implemented in insight toolkit (ITK). CT and FDG-PET images of 10 patients with liver metastases were registered rigidly a number of times. Results of the organ-focused method were compared to results of three commonly available methods (a manual, a landmark-based and a 'standard' mutual information-based method) where no dedicated image processing was performed. The proposed method outperformed the other methods with a precision (mean+/-s.d.) of 2.5+/-1.3 mm and a bias of 1.9 mm with a 95% CI of [1.0, 2.8] mm. Unlike the commonly available methods, our approach allows for robust CT-FDG-PET registration of the liver, with an accuracy better than the spatial resolution of the PET scanner that was used.