Study On 3D Cone-Beam CT Reconstruction Algorithm Acceleration

Cone-beam CT system can acquire multi-layer projection data in a single scanning circle by use of flat-panel detector system. Comparing with two-dimensional parallel and fan-beam CT, this system which now is widely applied, has the feature of short scanning time, high spatial resolution and efficient use of radiation. FDK algorithm which is proposed by Feldkamp, David and Kress based on circular scanning track is a practical reconstruction algorithm. At present, it is the most common algorithm in the commercial cone-beam CT system. However, with the number increasing of detector units and the scanning speed accelerating in the flat-panel system, as well as the complexity of three-dimensional reconstruction algorithm, the computation and the volume of data transmission in three-dimensional image reconstruction becomes huger and the algorithm is more and more time-consuming. The only use of CPU for image reconstruction calculation in past has been unable to meet the requirements of modern engineering applications. Now studying how to improve the computational speed and finding a suitable alternative method have an important value in application and academic research.In this paper, the content consists of two aspects. On the one hand, it is theory study of the cone-beam CT image reconstruction speed-up from the point of algorithm. On the other hand, it is the application of Compute Devices Unified Architecture (CUDA) in graphics processors to achieve FDK algorithm accelerating.In the study of reconstruction algorithm in cone-beam CT, this paper discusses three aspects based on the theory of FDK algorithm. First, this paper discusses the principle of parallel computation in the FDK algorithm. Although the computation is time-consuming, the algorithm can be calculated in parallel divided by the rotation angle or the sections in reconstructed object. Second, because the use of FPGA for cone-beam CT image reconstruction has been a hot spot in the field, so this paper discusses the back-projection calculation pipeline architecture which can cause the algorithm fast computation under the condition of small degree of parallel according to the back-projection calculation step. The simulation results in the computer show that the architecture can be constructed on FPGA. Third, the fixed-point back projection in FDK algorithm is discussed. Compared to the floating-point algorithm, the computer experiment results show that the relative error rate in fixed-point algorithm is less than 1%.In the applied research of the hardware reconstruction acceleration, this paper advances a speed-up method which uses CUDA in graphics processor (GPU) field. In this method, graphics card based on the new Hardware and software architecture is used. Through the new programming model in the architecture, the weighed, filtering and back-projection step is carried out by the Stream Processor Unit (SPU) in GPU, to achieve the FDK algorithm speed-up. The result shows that the image of 5123 volume in 512 rotation angles can be completed with 32bit floating-point in less than one minute, and the transmission time between the GPU and the computer memory is less than one second. This method gets a faster performance and good quality comparing with the method using CPU.