Abstract
For 3D radial data reconstruction in magnetic resonance imaging (MRI), fast Fourier transform via gridding (gFFT) is widely used for its fast processing and flexibility. In comparison, conventional 3D filtered back projection (cFBP), while more robust against common radial k-space centering errors, suffers from long computation times and is less frequently used. In this study, we revisit another back-projection reconstruction strategy, namely two-step 2D filtered back-projection (tsFBP), as an alternative 3D radial MRI reconstruction method that combines computational efficiency and certain error tolerance. In order to compare the three methods (gFFT, cFBP, and tsFBP), theoretical analysis was performed to evaluate the number of computational steps involved in each method. Actual reconstruction times were also measured and compared using 3D radial-MRI data of a phantom and a human brain. Additionally, the sensitivity of tsFBP to artifacts caused by radial k-space centering errors was compared with the other methods. Compared to cFBP, tsFBP dramatically improved the reconstruction speed while retaining the benefit of tolerance to the radial k-space errors. Our study therefore suggests that tsFBP can be a promising alternative to the conventional back projection method for 3D radial MRI reconstruction.
Highlights
For 3D radial data reconstruction in magnetic resonance imaging (MRI), fast Fourier transform via gridding is widely used for its fast processing and flexibility
A main goal of this study is to evaluate the computational performance of three different 3D radial-scan reconstruction methods: gFFT, conventional 3D filtered back projection (cFBP), and two-step 2D filtered back-projection (tsFBP)
Experiments were performed to demonstrate the robustness of the FBP approaches against simulated radial off-centering errors of the k-space trajectory, that can be caused by gradient delays, eddy currents, or finite digitization bandwidth, in comparison to gFFT
Summary
For 3D radial data reconstruction in magnetic resonance imaging (MRI), fast Fourier transform via gridding (gFFT) is widely used for its fast processing and flexibility. The RA scheme has recently gained popularity in the MR community due to the possibility of a shorter minimum echo time (TE) and better tolerance to motion and flow a rtifacts[2,3,4] as compared to conventional Cartesian k-space acquisition It is, sensitive to system imperfections such as timing delays between the actual and requested starting points of gradient w aveforms[5,6] because the readout direction in the k-space varies between repetitions. In terms of image reconstruction approaches, radial data can be reconstructed by two categories of reconstruction methods: 1) FFT via gridding (gFFT) and 2) filtered back-projection (FBP) based on the Radon t ransform[8]. Experiments were performed to demonstrate the robustness of the FBP approaches against simulated radial off-centering errors of the k-space trajectory, that can be caused by gradient delays, eddy currents, or finite digitization bandwidth, in comparison to gFFT. We considered only the most widely used, conventional gridding algorithm in gFFT for simplicity
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
