Thanks to the advances in parallel processing hardware, iterative algorithms for cone beam reconstruction are now available with computation times acceptable for clinical use. At the same time they are able to accomodate more accurately the physical effects underlying the X-Ray imaging process. Many parameters are involved, which need to be precisely calibrated in order to achieve an accurate 3D reconstruction. Unfortunately, some parameters might change individually for every cone beam acquisition, stirring the need for an online calibration technique. We present a method for automatically deriving individual parameter adjustements within an iterative reconstruction framework, without the need for a designated calibration phantom. Preliminary results on a beads phantom and anatomical sample show that self-calibration of global and local geometric parameters is possible; besides we briefly demonstrate radiometric calibration on phantom data.     «

Thanks to the advances in parallel processing hardware, iterative algorithms for cone beam reconstruction are now available with computation times acceptable for clinical use. At the same time they are able to accomodate more accurately the physical effects underlying the X-Ray imaging process. Many parameters are involved, which need to be precisely calibrated in order to achieve an accurate 3D reconstruction. Unfortunately, some parameters might change individually for every cone beam acquisit...     »