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 compulationally 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 0.53 +/- 12 mm for translation and 0.61 degrees +/- 0.29 degrees for rotation within the capture range.