School of Sciences, Changchun University, Changchun, 130012, China.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033, China.
Med Biol Eng Comput. 2018 Apr;56(4):635-648. doi: 10.1007/s11517-017-1709-8. Epub 2017 Aug 25.
Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.
从尽可能少的傅里叶采样中重建磁共振成像(MRI)一直是医学成像领域的一个难题。在我们的论文中,我们提出了一种基于导向滤波器的新方法,用于有效的 MRI 恢复算法。导向滤波器是一种边缘保持平滑算子,在边缘附近的性能优于双边滤波器。我们的重建方法由两个步骤组成。首先,我们提出了两个可以有效地计算的代价函数,从而得到两幅不同的图像。其次,利用这两幅得到的图像进行有效的边缘保持滤波,其中一幅图像作为导向图像,另一幅图像作为导向滤波器中的滤波图像。在我们的重建算法中,通过引入导向滤波器可以获得更多的细节。我们将我们的重建算法与一些有竞争力的 MRI 重建技术在 PSNR 和视觉质量方面进行了比较。给出了仿真结果,以显示我们新方法的性能。