Computed tomography (CT) is an imaging technique which produces cross sectional map of object from its projections. Image reconstruction algorithms require collection of projections covering the whole measurement range. Incomplete projection is still a hot research topic. This paper reviews the relationship between projection data and image reconstruction in computed tomography, and summarizes the effect of computed tomography on reconstruction quality. For the incomplete projection data acquired by different sampling strategies, the iterative algorithm is used to reconstruct the projection data. The effects of different data structures on the reconstructed image quality under uniform sampling and non-uniform sampling are studied, and the results are compared and analyzed. Meanwhile, the reasons of the reconstruction quality of the pros and cons are discussed in conjunction with the projection data distribution with different strategies. This paper provides a comprehensive sampling method for researchers in the field of CT reconstruction, and offers some ideas for the improvement of the corresponding algorithm for incomplete projection data. Furthermore, it also points out current focus of the study and research direction in future.