Point-based digitally reconstructed radiograph

In this paper, we present a novel point-based digitally reconstructed radiography (PBDRR) method for large CT data sets. Three steps are mainly included in the proposed method, namely point sampling, point rendering and quantization. Finite samples are determined on the nature or user-specified transfer function by a Monte Carlo technique. These samples are projected onto an image plane and the intensity value of each pixel records the count of samples projected onto the corresponding pixel area. The transfer function is related with the X-ray photon energy and the CT value. From the view of Monte Carlo integration, sufficient samples make the estimated pixel intensities believable theoretically. Moreover, PBDRR has O(N²) time complexity depending on the number of samples and is suitable for parallel processing and hardware acceleration. Some experimental results demonstrate the performance of the present method without redundant adjustments of the transfer function.