An important research problem in image-guided radiation therapy is how to accurately register daily onboard Cone-beam CT (CBCT) images to higher quality pretreatment fan-beam CT (FBCT) images. Assuming the organ segmentations are both available on CBCT and FBCT images, methods have been proposed to use them to help the intensity-driven image registration. Due to the low contrast between soft-tissue structures exhibited in CBCT, the interobserver contouring variability (expressed as standard deviation) can be as large as 2-3 mm and varies systematically with organ, and relative location on each organ surface. Therefore the inclusion of the segmentations into registration may degrade registration accuracy. To address this issue we propose a surface assimilation method that estimates a new surface from the manual segmentation from a priori organ shape knowledge and the interobserver segmentation error. Our experiment results show the proposed method improves registration accuracy compared to previous methods.
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