In computerized tomography, the cross-sectioned image of an object can be reconstructed from a set of projection data. It provides the ability to image internal structure which can not be inspected effectively with alternate techniques. Based on the Fourier slice theorem[l], projections in a full angular range and with sufficiently fine angular spacing are required to reconstruct a unique image. In some situations, however, complete projections are not available due to physical limitations in the data acquisition process. Image quality is degraded by the absence of complete data. Because most manufactured parts were built from a designer’s blueprint or solid modeling electronic database, a great deal is known about the physical structure of the part. Incorporating a priori information extracted from the CAD model has the potential to enhance incomplete projection CT image quality. In this paper, a model-based CT reconstruction method is presented. The a priori information used to enhance incomplete projection CT image quality is extracted from a 3-D solid modeling electronic database. Engineering database matching is conducted to extract the proper 2D cross-sectioned model image corresponding to the CT projection plane. A moment-based registration method is applied to ensure proper use of a priori information for model-based CT reconstruction. Furthermore, a projection substitution scheme, including projection alignment and automatic scaling method, is developed so that the projection data in the missing angular range calculated from a model image can be automatically rescaled to match the projection data in the available angular range. Experimental results of applying the model-based CT reconstruction method to an industrial part in both the limited-angle and the penetration-limited incomplete projection situations are presented and described. It is shown that the use of a priori information from solid models is a powerful technique for enhancing the quality of incomplete data CT images.