2 Capital University of Medical Sciences, Beijing,100872, P. R. China ; ... Magnetic resonance imaging (MRI) is widely used in medical diagnosis for its various ...
Fast iterative reconstruction method for PROPELLER MRI Hongyu Guo1, Jianping Dai2, Jinquan Shi3, 1 Sino-Dutch Biomedical and Information Engineering School Northeastern University, Shenyang,110004, P. R. China ; 2 Capital University of Medical Sciences, Beijing,100872, P. R. China ; 3 Philips and Neusoft Medical System Co.Ltd,Shenyang,110179, P. R. China ABSTRACT Patient motion during scanning will introduce artifacts in the reconstructed image in MRI imaging. Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) MRI is an effective technique to correct for motion artifacts. The iterative method that combine the preconditioned conjugate gradient (PCG) algorithm with nonuniform fast Fourier transformation (NUFFT) operations is applied to PROPELLER MRI in the paper. But the drawback of the method is long reconstruction time. In order to make it viable in clinical situation, parallel optimization of the iterative method on modern GPU using CUDA is proposed. The simulated data and in vivo data from PROPELLER MRI are respectively reconstructed in order to test the method. The experimental results show that image quality is improved compared with gridding method using the GPU based iterative method with compatible reconstruction time. Keywords: Magnetic Resonance Imaging, iterative reconstruction, motion artifacts, PROPELLER, GPU
1. INTRODUCTION Magnetic resonance imaging (MRI) is widely used in medical diagnosis for its various features, such as high-resolution [1]
capability, the ability to produce an arbitrary anatomic cross-sectioned image, and high tissue contrast .Body movements of restless, disoriented or injured patients, especially children and infants, are virtually unavoidable during conventional magnetic resonance data acquisition. AS a consequence, the resultant image quality is degraded by the imposition of a ghost-like artifact, blurring, and reducing the intensity of moving structures
[ 2]
. The only method for
[ 3]
and is often called motion detection and correction in widespread clinical use is based on the work of Pipe PROPELLER MRI. The PROPELLER method collects data in a series of rotating “blades” to fill the entire k-space (Fig. [ 3][ 4 ]
1). Each blade in k-space consists of several parallel lines acquired by the single-shot EPI or FSE technique . Two principal problems are very important in the research about PROPELLER MRI. One is how to improve the accuracy of rotation and translation correction and the other is how to efficiently improve image quality reconstructed from data after correction. Since more blades are overlapped in the center of k-space, the low frequencies are sampled more densely than the high frequencies. The fast Fourier transform (FFT), an efficient signal processing technique requiring uniform sampled data, cannot be applied to such nonuniformly sampled k-space directly. Many methods are proposed to reconstruct nonuniformly sample data. The most common reconstruction method is Kaiser-Bessel convolution gridding [ 3] [ 4 ]
method . First the data is pre-compensated for the varying density of the sampling and then the data is interpolated on a Cartesian grid with KaiserದBessel convolution kernel. Next, the data is transformed to the image domain with a FFT. Finally, a post-compensation stage is needed to correct for any rolloff introduced by the Fourier transform of the convolution function. However, in gridding method, the sampling density compensation is essential and must be chosen carefully. Moreover, a lot of parameters have to be optimized such as the convolution window width, the shape parameter and the overgridding factor
[ 5 ][ 6 ]
. Otherwise, they become the major source of degrading reconstructed image
quality. In recent years, iterative method has attracted much attention due to better reconstructed image quality
MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, edited by Jianguo Liu, Kunio Doi, Aaron Fenster, S. C. Chan, Proc. of SPIE Vol. 7497, 74972O © 2009 SPIE · CCC code: 0277-786X/09/$18 · doi: 10.1117/12.831244 Proc. of SPIE Vol. 7497 74972O-1
[ 7 ][8 ]
.But
these method is computationally expensive. So they have been impractical in clinical setting particularly for large-scale problems such as PROPELLER MRI. In this paper, the iterative method implemented on GPU using CUDA is applied to PROPELLER MRI reconstruction. The purpose of this paper is solving the later of two problem mentioned before.
Figure 1. Trajectory of PROPELLER
2. METHOD 2.1 NUFFT The basic idea of NUFFT (nonuniform fast Fourier transform) is to first compute an oversampled FFT of the given signal, and then optimally interpolate onto the desired nonuniform frequency locations using small local neighborhoods [ 9 ][10 ][11]
in the frequency domain around each desired value problem. Given equally spaced samples xn , for n
. For simplicity, we restrict our attention to the 1-D NUFFT
N / 2,..., N / 2 1 .An efficient approximation of the discrete time Fourier transform (DTFT) of this sequence at the non-uniform frequency locations vm , for m 1,2,..., M is: N /2
ym
X (vm )
¦x e
inwm
(1)
n
n N / 2
In matrix notation:
Y
