摘 要
压缩感知的磁共振成像重建算法主要应用在医学临床行业，临床诊断都会运用到压缩感知的磁共振成像重建算法系统或仪器。更高效率和更高精度的压缩感知的磁共振成像重建算法一直是研究的热点。在医院的临床医学中，压缩感知的磁共振成像重建算法随处可见，因为其相比其他的控制方式而言，运行稳定且控制精度较高等优势，最重要的是压缩感知的磁共振成像重建算法在成像质量等方面具有很好的优势。随着自动控制技术和微电子技术的不断革新，目前的技术水平为实现压缩感知的磁共振成像重建算法调节控制打下坚实的基础，提供扎实的理论依据。
磁共振成像是一种非介入式成像方法，具有安全、成像质量高等特点，为临床诊断提供了丰富的信息，已成为临床医学检查的重要手段之一。但扫描时间长、成像速度慢是磁共振成像的主要缺点，影响了它的进一步推广和应用。受奈奎斯特采样频率的限制，传统的磁共振加速采样方法对磁共振扫描速度提高有限。由Donoho和 Candès等提出的压缩感知理论突破了这个限制，其采样频率能够远低于奈奎斯特频率，这为加速磁共振成像提供了一个新的方向。
本次设计主要以压缩感知的磁共振成像重建算法控制系统设计应用作为研究背景，运用MATLAB仿真工具编写相应的仿真程序。该程序利用MATLAB软件中的模块库，建立了压缩感知的磁共振成像重建算法在临床医学应用中的系统仿真程序，通过 Matlab仿真软件编写仿真程序,运行仿真，并对压缩感知的磁共振成像重建算法的仿真结果进行了分析。本次设计采用的压缩感知的磁共振成像重建算法，经过对控制系统进行仿真，可以明显的看出，压缩感知的磁共振成像重建算法能够提高磁共振重建图像质量，缩短算法执行时间，加快磁共振成像速度。
关键词：压缩感知，磁共振成像，仿真 ，MATLAB
Abstract
The mri reconstruction algorithm of compressed sensing is mainly applied in the medical clinical industry, and the mri reconstruction algorithm system or instrument of compressed sensing is used in clinical diagnosis. Mri reconstruction algorithm with higher efficiency and higher precision is always a research hotspot. In clinical medicine of hospitals, compressed sensing mri reconstruction algorithm can be seen everywhere, because compared with other control methods, it has the advantages of stable operation and higher control accuracy. The most important is that the compressed sensing MRI reconstruction algorithm has good advantages in imaging quality and other aspects. With the continuous innovation of automatic control technology and microelectronics technology, the current technical level has laid a solid foundation and provided a solid theoretical basis for the adjustment and control of compressed sensing mri reconstruction algorithm.
Magnetic resonance imaging is a non-interventional imaging method, which has the characteristics of safety and high imaging quality. It provides abundant information for clinical diagnosis and has become one of the important means of clinical medical examination. However, long scanning time and slow imaging speed are the main disadvantages of MRI, which affect its further popularization and application. Due to the limitation of Nyquist sampling frequency, the speed of magnetic resonance scanning is limited by the traditional accelerated sampling method. The compressed sensing theory proposed by Donoho and Candes et al. breaks through this limitation, and its sampling frequency can be much lower than Nyquist frequency, which provides a new direction for accelerated magnetic resonance imaging.
This design mainly to compress sensing magnetic resonance imaging reconstruction algorithm control system design and application as the research background, using MATLAB simulation tools to write the corresponding simulation program. This program uses the module library of MATLAB software to establish the system simulation program of compressed sensing magnetic resonance imaging reconstruction algorithm in clinical medical application. The simulation program is written and run by MATLAB simulation software, and the simulation results of the compressed sensing magnetic resonance imaging reconstruction algorithm are analyzed. The magnetic resonance imaging reconstruction algorithm of compressed sensing used in this design, through the simulation of the control system, it can be obviously seen that the magnetic resonance imaging reconstruction algorithm of compressed sensing can improve the image quality of magnetic resonance reconstruction, shorten the algorithm execution time and speed up magnetic resonance imaging.
Key words: Compressed sensing, Magnetic resonance imaging, Simulation, MATLAB
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