Purpose Deformable registration of ultrasound (US) and contrast enhanced computed tomography (CECT) images are essential for quantitative comparison of ablation boundaries and dimensions determined using these modalities. This comparison is essential as stiffness‐based imaging using US has become popular and offers a nonionizing and cost‐effective imaging modality for monitoring minimally invasive microwave ablation procedures. A sensible manual registration method is presented that performs the required CT‐US image registration. Methods The two‐dimensional (2D) virtual CT image plane that corresponds to the clinical US B‐mode was obtained by “virtually slicing” the 3D CT volume along the plane containing non‐anatomical landmarks, namely points along the microwave ablation antenna. The initial slice plane was generated using the vector acquired by rotating the normal vector of the transverse (i.e., xz) plane along the angle subtended by the antenna. This plane was then further rotated along the ablation antenna and shifted along with the direction of normal vector to obtain similar anatomical structures, such as the liver surface and vasculature that is visualized on both the CT virtual slice and US B‐mode images on 20 patients. Finally, an affine transformation was estimated using anatomic and non‐anatomic landmarks to account for distortion between the colocated CT virtual slice and US B‐mode image resulting in a final registered CT virtual slice. Registration accuracy was measured by estimating the Euclidean distance between corresponding registered points on CT and US B‐mode images. Results Mean and SD of the affine transformed registration error was 1.85 ± 2.14 (mm), computed from 20 coregistered data sets. Conclusions Our results demonstrate the ability to obtain 2D virtual CT slices that are registered to clinical US B‐mode images. The use of both anatomical and non‐anatomical landmarks result in accurate registration useful for validating ablative margins and comparison to electrode displacement elastography based images.