【作者】 侯正松；

【导师】 陈武凡；

【作者基本信息】 第一军医大学 ， 生物医学工程， 2004， 硕士

【摘要】 随着近年来磁共振成像技术在临床医学诊断和治疗中发挥的作用越来越大，对如何矫正临床磁共振(MR)图像中存在的伪影的研究显得较为迫切。运动伪影是临床MR图像中几种较为常见的伪影之一，在通过硬件设备的改进和抑制运动的产生等前处理方法对运动伪影矫正效果不甚理想的情况下，使用计算机技术来矫正运动伪影的后处理算法研究就显得尤为重要。但由于运动的多样性和运动伪影形成的复杂性，使得研究很难开展，当前只是对理想模型在理想状态产生的MR图像中的运动伪影进行了探索性的研究，为将来的临床MR图像运动伪影的矫正技术研究打下基础。本文同样对理想的刚性运动造成的MR图像运动伪影的矫正展开研究，提出了一种新的、更为快速的伪影矫正算法：逆向迭代矫正法(ⅡC)。 在K空间通过逆向模拟目标的运动，对原始数据产生相反的相位偏移，以补偿原来已经偏移的相位，对各种类型的运动(包括周期性的和随意性的)产生的相位偏移都可用此方法进行补偿。如果能够确保存在某一模拟的运动与目标的真实运动恰好是一对逆运动(大小相等，方向相反)，就能完全矫正原有的相位偏移。 基于图像自身直方图的熵约束函数，更好地利用了图像本身的信息，提高了对逆向运动方向和距离约束的精确性，同时使得运算速度得到较大的提高。 在本文ⅡC算法矫正过程中，运用了运动的连续性和一致性，对K空间线(K-space view)先矫正后约束，然后通过熵约束准则恰当地判断出运动方向的改变点，这种快速而优化的矫正策略极大地提高矫正精度和缩短矫正所需的时间。 本文对所提ⅡC算法做了大量的实验，通过实验比较，验证了本文所提算法的精确性和有效性。更多还原

【Abstract】 In the recent years, there are urgent needs of the research on artifact correction in a magnetic resonance imaging (MRI) scan with its rapidly increasing great effect on clinic diagnosis and therapy. Especially, the research on motion artifact correction with post-processing algorithm is one of the most important fields in the case of that there are not very ideal methods to suppress MRI artifacts by means of the development of hardware and the pre-processing methods based on restraining motion happening. However, the state-of-the-art approaches on motion artifact correction are only implemented with the ideal motion model in the ideal conditions for the variety and complexity of the motion-happening causes in the real world. In this paper, a novel and fast algorithm for artifact correction, the inverse iterative correction (IIC) technique is proposed to reduce motion artifact due to simulated ideal rigid motion in MR images.In order to correct the phase errors due to all kinds of motions (including the periodic and the random), some inverse phase errors due to the simulated motion can be added to the raw data in k-space to counteract the original phase errors. If some simulated motion is right reverse to the real motion (same magnitude in opposite direction), the original phase errors can be surely cured.Thus, the histogram-based entropy function proposed in this article, utilizing the image own grey scale information in image domain, can not only better estimate the actual direction and displacement of patient motion as well, but also greatly improve the computational process.In the correction process of IIC, k-space lines are processed in the manner of direct correction-and-judgment according to continuity and consistency of the motion ,thereby, the change point of the motion can be properly estimate with the entropy criterion. The optimized correction strategy is verified to obviously improve the accuracy of correction and decrease the computational time.A lot of experiments and results of comparison with the other method are provided in this paper to demonstrate the feasibility and advantage of the proposed IIC method.更多还原