Dynamic X-ray Computed Tomography (CT) is an attractive imaging technology for the guidance in minimal invasive surgery. In this field, projection data simulation is an important tool to optimise scanner geometry and to validate reconstruction algorithms. A realistic simulation software, called “Sindbad” has been developed to compute 2D projections. It is based on an analytical model and allows simulating X-ray emission, attenuation through an examined
object and photon detection. New functionality has been added to simulate a virtual scanner and to combine 2D projections from CAD phantoms with CT data volumes. Phantoms can be animated with independent motion and temporal evolution laws. CT data can be deformed over time by using a Free Form Deformation (FFD) technique.
Encouraging results have been obtained for the simulation of a lung biopsy. To simulate breathing, CT lung data are animated by using a respiratory law. Biopsy needle was inserted along a straight line from an entry point to a target point at a regular speed. The guidance direction also varied with time according to the respiration law. Similar simulations are also used to validate dynamic reconstruction algorithm for radiotherapy planning.
The cone beam X-ray transform modelizes the measurements on new 3D medical imaging devices using 2D detectors, for instance X-ray transmission tomographs using image intensifiers or gamma-ray emission tomographs using convergent collimators. The most commonly used reconstruction algorithm performs cone beam back projection (FELDKAMP 1984). But it induces some distortions for objects far from the plane of the cone apex. We have established an exact formula between the cone beam X-ray transform and the first derivative of the 3D Radon transform (GRANGEAT 1987). It shows that the distortions are induced by the shadow zone in the Radon domain related to the planes which intersect the object but not the apex trajectory. In the Radon domain, it becomes possible to restore the missing information by interpolation. Then the reconstruction principle is to compute and to invert the first derivative of the Radon transform. In this communication, we compare these two algorithms on reconstructions performed on simulated acquisitions. We study the shape and level distortions along lines parallel to the rotation axis. We present an analysis of the axial and radial variations of the Modulation Transfer Function (MTF) and of their distortions. We conclude that the Radon transform algorithm provides a regularized solution to the distortions, with optimized computing time on modern scientific computers.