Abstract:
Data processing systems (DPS) and related methods for nuclear medicine imaging. At an input interface (IN), first projection data (λ), or a first image (V) reconstructable from the first projection data, is received. The first projection data is associated with a first waiting period (ΔT*). The first waiting period indicates the time period from administration of a tracer agent to a start of acquisition by a nuclear medicine imaging apparatus (IA) of the projection date. A trained machine learning module (MLM) estimates, based on the first projection data (λ) or on the first image (V), a second projection data (λ′) or a second image (V′) associable with a second waiting period (ΔT), longer than the first waiting period (ΔT*). Nuclear imaging can thus be conducted quicker. Similar machine learning based data processing systems and related methods are also envisaged to reduce acquisition time periods or the time it takes to reconstruct imagery.
Abstract:
A method and apparatus are provided to improve large field of view CT image acquisition by using at least two scanning procedures: (i) one with the radiation source and detector centered and (ii) one in an offset configuration. The imaging data obtained from both of the scanning procedures is used in the reconstruction of the image. In addition, a method and apparatus are provided for detecting motion in a reconstructed image by generating a motion map that is indicative of the regions of the reconstructed image that are affected by motion artifacts. Optionally, the motion map may be used for motion estimation and/or motion compensation to prevent or diminish motion artifacts in the resulting reconstructed image. An optional method for generating a refined motion map is also provided.