Enhancing skeletal features in digitally reconstructed radiographs

Abstract

Generation of digitally reconstructed radiographs (DRR) is a critical part of 2D-3D image registration that is utilized in patient position alignment for image-guided radiotherapy and radiosurgery. The DRRs are generated from a pre-operative CT scan and used as the references to match the X-ray images for determining the change of patient position. Skeletal structures are the primary image features to facilitate the registration between the DRR and X-ray images. In this paper, we present a method to enhance skeletal features of spinal regions in DRRs. The attenuation coefficient at each voxel is first calculated by applying an exponential transformation of the original attenuation coefficient in the CT scan. This is a preprocessing step that is performed prior to DRR generation. The DRR is then generated by integrating the newly calculated attenuation coefficients along the ray that connects the X-ray source and the pixel in the DRR. Finally, the DRR is further enhanced using a weighted top-hat filter. During the entire process, because there is no original CT information lost, even the small skeletal features contributed by low intensity part of CT data are preserved in the enhanced DRRs. Experiments on clinical data were conducted to compare the image quality of DRRs with and without enhancement. The results showed that the image contrast of skeletal features in the enhanced DRRs is significantly improved. This method has potential to be applied for more accurate and robust 2D-3D image registration.