A set of experiments were conducted to evaluate six similarity measures for intensity-based rigid-body 3D/2D image registration. Similarity measure is an index that measures the similarity between a digitally reconstructed radiograph (DRR) and an x-ray planar image. The registration is accomplished by maximizing the sum of the similarity measures between biplane x-ray images and the corresponding DRRs in an iterative fashion. We have evaluated the accuracy and attraction ranges of the registrations using six different similarity measures on phantom experiments for head, thorax, and pelvis. The images were acquired using Varian Medial System On-Board Imager. Our results indicated that normalized cross correlation and entropy of difference showed a wide attraction range (62 deg and 83 mm mean attraction range, ω_mean), but the worst accuracy (4.2 mm maximum error, e_max). The gradient-based similarity measures, gradient correlation and gradient difference, and the pattern intensity showed sub-millimeter accuracy, but narrow attraction ranges (ω_mean=29 deg, 31 mm). Mutual information was in-between of these two groups (e_max=2.5 mm, ω_mean= 48 deg, 52 mm). On the data of 120 x-ray pairs from eight IRB approved prostate patients, the gradient difference showed the best accuracy. In the clinical applications, registrations starting with the mutual information followed by the gradient difference may provide the best accuracy and the most robustness.

Key words: 3D/2D image registration; Similarity measures; Patient positioning; and Image guided radiation therapy.