The Study Of Incomplete Projection CT Reconstruction Based On Gray System

Computed tomography (CT) is a technique for imaging cross-sections of an object using a series of X-ray measurements. It has been widely applied in diagnostic medicine and industrial non-destructive testing. Computed Tomography is one of the advanced means for non-destructive testing, which has the virtues of non-destructive, non-contact and high resolution. With the wide application of CT, reconstruction algorithm has become the focus of many studies.The researches in this paper fall into two parts: Incomplete projection reconstruction and multi-ART (Algorithm Reconstruction Technique).At present, most of the CT systems need complete projections of data, but it is difficult to obtain complete projections for many reasons. In view of this point, this paper studies three incomplete data problems (the exterior problem, the interior problem and the limited angle problem) of computed tomography. The incomplete data problems may be caused by many factors, such as, the equipment and the density region of detected objects. Therefore, it is essential to explore a new universal method approaching to the incomplete data problems. This paper introduces a new method of completion which builds dynamic differential equations to predict other unknown data based on the gray system theory, and we can exploit FBP to solve the incomplete data problems. Compared to other local tomography algorithms, this method has reduced the amount of radiation. Moreover, it's more efficiently to solve above problems. Hence the method of completion based on GM(1,1) model can be widely applied in practice.The other work of the paper is multi-ART reconstruction on the local area network (LAN). As the cost of ART is very big, to obtain acceptable reconstruction time, optimization is very necessary. But there are some limits. A new method based on the LAN is presented to improve the speed in this paper. The shared buffer, in which the data file is used, is created in the master computer, and the master computer and the slave computer can exchange information. After the slave computers send the results to the shared buffer, the final reconstruction is got by the master computer using different image fusion algorithms. It's simple and easy to implement, and the reconstruction time can be reduced greatly.