GPU-accelerated few-view CT reconstruction using the OSC and TV techniques

The present work proposes a promising iterative reconstruction technique designed specifically for X-ray transmission computed tomography (CT). The main objective is to reduce diagnostic radiation dose through the reduction of the number of CT projections, while preserving image quality. The second objective is to provide a fast implementation compatible with clinical activities. The proposed tomographic reconstruction technique is a combination of the Ordered Subsets Convex (OSC) algorithm and the Total Variation minimization (TV) regularization technique. The results in terms of image quality and computational speed are discussed. Using this technique, it was possible to obtain reconstructed slices of relatively good quality with as few as 100 projections, leading to potential dose reduction factors of up to an order of magnitude depending on the application. The algorithm was implemented on a Graphical Processing Unit (GPU) and yielded reconstruction times of approximately 185 ms per slice. (orig.)