FPGA Acceleration for 3-D Low-Dose Tomographic Reconstruction

X-ray computed tomography (CT) is commonly used to obtain vivo images to characterize diseases but results in radiation exposure to patients. Low-dose CT (LDCT) provides CT images of clinical quality with reduced cumulative radiation dose. Iterative image reconstruction methods with effective regularization are used for LDCT but generally require more computing resources and induce higher computational load than the conventional filtered backprojection (FBP) methods. The high computational demand of the iterative reconstruction (IR) with notably increased reconstruction time precludes its routine clinical application. In this work, we focus on the FPGA acceleration of a compute-intensive full IR (full-IR) algorithm based on the Mumford-Shah regularization. At the algorithmic level, we propose a beam-based asynchronous update algorithm to reduce the computational cost and alleviate the conflicts. At the hardware-level, we first present pipeline-friendly optimization for the original algorithm to increase the computation throughput. We then apply the LDCT-specific tiling strategy to improve the data reuse rate. The experimental results show that our implementation takes 8.5 min to reconstruct a typical physical phantom with the image quality comparable with the vendor's result. The FPGA implementation achieves 11.6x throughput against the state-of-the-art GPU version.