Optimal computed tomography data acquisition techniques and filter selection for detection of small density variations

Accurately measuring small relative density variations within the interior of an object using computed tomography requires special considerations. Data acquisition techniques and filtering must be optimized as a whole to obtain optimal results. It is shown that using the filtered back-projection reconstruction algorithm, a combination of oversampling, 360-degree data acquisition, data averaging, and a common reconstruction filter can substantially improve image quality. The effect of each of these techniques on image quality is documented with extensive simulations. Images from reconstructions of data obtained from a computed tomography system are presented and analyzed to support the results of the simulations.