Reconstruction Of Images From Magnetic Resonance Truncated Data

Magnetic Resonance Imaging (MRI) is a scatheless diagnose means which has much more virtue than other imaging methods such as X-CT. So it is now used widely. But normal MRI often costs long time (about several minutes) , that leads high costs. The movement of the patient makes the image blur and contrast distortion. So it cannot be used to research movement organs and nerve system. Also the function MRI arised these years required high speed of MRI. To shorten imaging time in clinic application, partial k-space method is often used which is an efficiency imaging way using reduced scan data. This method can short imaging time without changing the hardware of MRI and the scan way. It is a fast imaging way with low cost. However, reduction of the number of phase-encoded signals results in the truncation artifacts when the truncated k-space data is Fourier transformed to reconstruct the image.The truncation artifact has long been a hindrance to the image reconstruction. So far some methods to reduce truncation artifacts have been proposed. Filters are often introduced to reduce the effects of the truncation artifacts, but filtering inevitably causes blurring of the features of the reconstructed image at the boundaries. In the recent years, there are urgent needs as to how to remove truncation artifacts in a magnetic resonance imaging research. The purpose of this study is to reduce the truncation artifacts and improve the quality of MR image with partial k-space. In this paper, a novel and accurate algorithm, namely the Equation System Solving-Based Singularity Function Analysis, is proposed to eliminate the truncation artifacts.Singularity Function Analysis method was proposed in recent years, and has been shown to effectively eliminate the effects of truncation...