WE-E-213CD-04: CT to Cone-Beam CT Deformable Registration With Simultaneous Intensity Correction.

PURPOSE

To develop and validate a robust CT to cone-beam (CBCT) deformable image registration algorithm that can handle CBCT artifacts and intensity inconsistency, and thus can yield accurate registration results.

METHODS

We propose a new algorithm called Deformation with Intensity Simultaneously Corrected (DISC). DISC distinguishes itself from the original demons by performing an intensity correction procedure on the CBCT image at every iteration step of demons registration. Specifically, the intensity correction of a voxel in CBCT is achieved by matching the first and the second moments of the image intensities inside a patch around this voxel with those on the CT image. It is expected that such a strategy can remove artifacts in the CBCT image, as well as ensuring the intensity consistency between the two modalities and hence facilitating the registration process. DISC is implemented on computer graphics processing units (GPUs) using the compute unified device architecture (CUDA) programming environment. The performance of DISC has been qualitatively and quantitatively evaluated on a simulated patient case and six head-and- neck cancer patient data.

RESULTS

Visual inspection shows that original demons distorts the tissues after registration, especially in regions which are heavily degraded by artifacts. DISC, on the other hand, can effectively register CT and CBCT image even in regions contaminated by severe artifacts. The intensity corrected CBCT that extracted from the last iteration of DISC is artifact-free and has similar histogram distribution with the deformed CT.

CONCLUSIONS

We have developed a robust CT to CBCT deformable image registration method that properly deals with the CBCT artifacts and intensity inconsistency, and thus yields accurate registration results. This work is supported in part by the University of California Lab Fees Research Program, the Master Research Agreement from Varian Medical Systems, Inc., and the grants from the National Natural Science Foundation of China (No.30970866).