Automatic 3D-2D image registration using partial digitally reconstructed radiographs along projected anatomic contours

The paper presents a new intensity-based 3D-2D image registration algorithm for automatic pretreatment validation in radiotherapy. The novel aspects of the algorithm includes a hybrid cost function developed based on partial digitally reconstructed radiographs (DRRs) generated along projected anatomic contours and level set for similarity measurement, and a fast search method developed based on parabola fitting and sensitivity based search order. Using CT and orthogonal X-ray images from a skull phantom, the proposed algorithm is compared with the conventional ray-casting full DRR based registration method. Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error) and high registration accuracy with average errors of 0.53plusmn 0.12 mm for translation and 0.61degplusmn0.29deg for rotation within the capture range.