Analysis of Compressed Sensing Based CT Reconstruction with Low Radiation

The property of the system matrix of fan-beam computed tomography (CT) is investigated to achieve low radiation dose while reserve good reconstruction quality through compressed sensing (CS). To reduce the radiation dose, scanning data is under-sampled in both the view and bin direction. For limited-angle scanning, two sampling patterns are adopted: golden-angle and random-angle. For sparse bin setting, the reduced detectors are either evenly or randomly distributed. The analysis is conducted based on point spread function (PSF) and Fourier slice theorem (FST), respectively. The simulation results verify the correctness of the analysis and it is shown that low radiation CT reconstruction can be achieved with random detectors and golden-angle scanning.