| Clinical diagnosis and security detection tasks increasingly require 3D (three dimensional) information that is difficult or impossible to obtain from 2D (two dimensional) radiographs. As a 3D non-destructive radiographic imaging technique, digital tomosynthesis is especially fit for cases where complete projection data is not available. Tomosynthesis is an economical and efficient 3D imaging technique. The reconstruction simply involves shifting and adding processes. With the development of high resolution flat panel digital detectors, tomosynthesis can generate images with higher resolution than current CT using only a limited number of projections taken from limited view directions.; FBP (filtered back projection) is extensively used in industry for its fast speed and simplicity. However, it yields poor results in situations where only a limited number of cone beam projections from constrained directions are available, or the SNR (signal to noises ratio) of the projections is low. In order to solve these problems, several image reconstruction methods are presented in this dissertation.; A set of fiducial balls are utilized to obtain the accurate data acquisition geometry. This allows unconstrained projection acquisition, thus making portable and relatively cheap tomosynthesis equipment possible.; A statistical reconstruction method is described based on the acquisition model of X-ray projections. We formulate a ML (maximum likelihood) function for this model and develop an ordered-subsets iterative algorithm to estimate the unknown attenuation of the object. Simulations show that satisfactory results can be obtained after 1 to 2 iterations. Applying these methods to computer generated phantom and true projections from diagnostic radiographs yields reconstruction with a high contrast and low noise. Layer driven parallel programming with shared memory is also implemented and tested. The quality of the reconstructed object is preserved, while the computation time is reduced by almost the number of threads used.; Sharpness and clearness are two very important evaluation criteria for the quality of the reconstructed images. This dissertation discusses the major factors such as number of projections, and the projection angles that influence the image quality. In addition, this dissertation describes the calibration methods for tomosynthesis which can suppress the fixed pattern noise and the electronic random noises. |
