Simulation of anatomical texture in voxelized XCAT phantoms
While great advances are made toward making highly realistic, surface models of the human anatomy, very little has been done to fill these bounded surfaces with models of anatomical texture. We propose a method whereby realistic anatomically-based computed tomography (CT) texture can be incorporated into voxelized versions of the 4D extended cardiac-torso (XCAT) phantom. Our source of texture comes from patient CT scans from the Duke CT imaging database. These image-sets were de-noised using anisotropic diffusion. Two organs were selected from which texture was obtained, liver and lungs. From each organ, multiple regions of interest (ROIs) were taken and tiled side-by-side to create a larger image. Textures for the liver and lungs were extrapolated using ImageQuilting, based on the tiled images. Next, a NURBSbased XCAT phantom was voxelized at the same resolution as the textures. The texture was then placed in the voxelized phantoms. Finally, CT simulations of the phantoms with and without the textures were compared against each other, using the power spectral density. This work shows that there is a way whereby the XCAT phantoms can be textured to give more realistic appearance in CT simulations. It is anticipated that this method would find great use in making projections of the XCAT phantom look more realistic and allow for the phantoms to not only be utilized in dosimetrical evaluations, but in image quality studies as well. © 2013 SPIE.
