FPGA-based Hardware Accelerator for Image Reconstruction in Magnetic Resonance Imaging (Abstract Only)

Abstract

Magnetic Resonance Imaging (MRI) is widely used in medical diagnostics. Sampling of MRI data on Cartesian grids allows efficient computation of the Inverse Discrete Fourier Transform for image reconstruction using the Inverse Fast Fourier Transform (IFFT) algorithm. Though the use of Cartesian trajectories simplifies the IFFT computation, non-Cartesian trajectories have been shown to provide better image resolution with lower scan times. To improve the processing time of MRI image reconstruction for these optimized non-Cartesian trajectories using a Non-uniform Fast Fourier Transform (NuFFT) algorithm, dedicated accelerators are required. We present an FPGA-based MRI solution to implement NuFFT for image reconstruction. The solution is based on the design of an efficient custom accelerator on FPGA using OpenCL, and covers all the phases necessary to reconstruct an image with high accuracy, starting from raw scan data. The architecture can be easily extendable to tackle 3D imaging, and k-space properties have been analyzed to reduce the number of samples processed, achieving satisfactory reconstruction accuracy while positively impacting processing time. Our solution achieves a marked improvement over previously published FPGA- and CPU-based implementations and, due to its scalability, it is suitable for the image sizes common in MRI acquisitions.