We have developed an automated technique to accurately register the CT and SPECT scans of the liver of patients treated with radioactive microspheres for tumour targeting assessment. An anthropomorphic phantom was used to validate the accuracy of the registration algorithm. The phantom liver and three fiducial markers placed on its surface were filled with 99mTc. The phantom was scanned with CT and SPECT scanners in different positions. The liver volume was contoured on the CT scans from which a three-dimensional liver mask was created. By constraining the liver volume to the volume obtained from the CT scans, another liver mask was automatically created from the SPECT images. An adaptive simulated annealing algorithm was used to minimize the difference between the two volumes formed by the two sets of masks. The algorithm involved rigid transformation of the SPECT mask to reach the optimization goal. The accuracy of the algorithm was evaluated by the superposition of the fiducial markers on the CT and SPECT. The registered SPECT overlaid on the CT scan of the phantom showed congruence of the fiducial markers on CT and SPECT images within 1 mm. The technique was applied to a patient image set who received the microsphere infusion procedure. The registered CT and SPECT images of the patient showed that the majority of the activity was concentrated in the tumour, indicating a successful tumour targeting.