Magnetic-resonance image segmentation based on improved variable weight multi-resolution Markov random field in undecimated complex wavelet domain

To solve the problem that the magnetic resonance (MR) image has weak boundaries, large amount of information, and low signal-to-noise ratio, we propose an image segmentation method based on the multi-resolution Markov random field (MRMRF) model. The algorithm uses undecimated dual-tree complex wavelet transformation to transform the image into multiple scales. The transformed low-frequency scale histogram is used to improve the initial clustering center of the K-means algorithm, and then other cluster centers are selected according to the maximum distance rule to obtain the coarse-scale segmentation. The results are then segmented by the improved MRMRF model. In order to solve the problem of fuzzy edge segmentation caused by the gray level inhomogeneity of MR image segmentation under the MRMRF model, it is proposed to introduce variable weight parameters in the segmentation process of each scale. Furthermore, the final segmentation results are optimized. We name this algorithm the variable-weight multi-resolution Markov random field (VWMRMRF). The simulation and clinical MR image segmentation verification show that the VWMRMRF algorithm has high segmentation accuracy and robustness, and can accurately and stably achieve low signal-to-noise ratio, weak boundary MR image segmentation.     

Nonlinear profile order for three-dimensional hybrid radial acquisition applied to self-gated free-breathing cardiac cine MRI

This paper presents a nonlinear profile order scheme for three-dimensional(3D) hybrid radial acquisition applied to self-gated, free-breathing cardiac cine magnetic resonance imaging(MRI). In self-gated, free-breathing cardiac cine MRI,respiratory and cardiac motions are unpredictable during acquisition, especially for retrospective reconstruction. Therefore,the non-uniformity of the k-space distribution is an issue of great concern during retrospective self-gated reconstruction. A nonlinear profile order with varying azimuthal increments was provided and compared with the existing golden ratio-based profile order. Optimal parameter values for the nonlinear formula were chosen based on simulations. The two profile orders were compared in terms of the k-space distribution and phantom and human image results. An approximately uniform distribution was obtained based on the nonlinear profile order for persons with various heart rates and breathing patterns.The nonlinear profile order provides more stable profile distributions and fewer streaking artifacts in phantom images. In a comparison of human cardiac cine images, the nonlinear profile order provided results comparable to those provided by the golden ratio-based profile order, and the images were suitable for diagnosis. In conclusion, the nonlinear profile order scheme was demonstrated to be insensitive to various motion patterns and more useful for retrospective reconstruction.     

三维多回波流动补偿定量磁化率成像(QSM)方法研究

定量磁化率成像(QSM)利用一般成像技术舍弃的相位信息得到局部磁场变化特性,通过复杂的场到源反演计算,可直接得到定量的磁化率图,它广泛应用于测量血氧饱和度、脑部微出血、铁沉积、组织钙化等方面．然而,梯度磁场中流动会引起相位错误,并且产生显著的流动伪影,最终得到错误的QSM图像．为了矫正流动的影响,该文在3 T磁共振系统上实现了三维多回波流动补偿梯度回波序列,并用该序列采集流动水模和志愿者颅脑数据．流动水模和颅脑数据均显示,流动补偿能够明显矫正相位错误,消除流动伪影．颅脑横断位QSM结果证明,流动补偿序列可以消除血液流动引起的QSM的错误,提高QSM的准确性．     

定量磁化率成像多回波相位拟合算法研究

定量磁化率成像(quantitative susceptibility mapping,QSM)技术大多采用多回波梯度回波序列采集相位数据,经加权最小二乘法(weighted linear least-square,WLS)拟合得到局部磁场分布.对于组织磁化率分布不均匀的区域,尤其是颅底部位,常规WLS算法拟合得到的局部磁场误差较大,导致相应部位磁化率分布图信噪比较低.针对常规WLS算法的这一不足,该文提出了一种截断WLS算法.对两种算法拟合得到的磁化率分布图对比研究发现,截断WLS算法可有效提高颅底部位定量磁化率分布图的图像质量,使其噪声明显下降.     

定量肝脏脂肪的波谱自动后处理算法

目前质子磁共振波谱技术可用于肝脏脂肪含量的定量检测.利用快速T₂校正多回波波谱采集序列可一次屏气获得一组不同回波时间的波谱数据,然后通过谱线拟合和分析得到质子密度脂肪分数.波谱数据后处理一般通过第三方软件,处理步骤复杂,需要消耗大量的时间,而且有不可避免的人为控制因素干扰.本文开发了自动波谱后处理算法,可以实现谱线拟合、T₂衰减校正和脂肪分数计算,并进一步采用水脂模型实验和人体肝脏脂肪检测实验对算法的可行性和准确性进行了评估.研究结果显示,本文提出的自动定量算法计算得到的质子密度脂肪分数和jMRUI软件处理得到的结果高度一致,但其操作简单,更适用于脂肪肝临床检测.     

基于复值和模值的肝脏磁共振水脂分离组合算法

质子密度脂肪分数（proton density fat fraction,PDFF）是用于评估肝脏脂肪的重要定量指标.为了获得更为精确的肝脏PDFF,本文通过分离R₂^*估计,提出了一种改进的基于磁共振成像（magnetic resonance imaging,MRI）脂肪定量方法.通过在3.0 T MRI扫描仪器上对肝脏脂肪含量不同的人体被试进行MRI扫描,进一步验证了该方法的可行性和准确性.研究结果显示,本文方法得到的肝脏脂肪分数和磁共振波谱（magnetic resonance spectroscopy,MRS）分析得到的脂肪含量高度一致,表明该方法对临床脂肪肝的检测具有重要的参考指导价值.     

Accuracy and effectiveness of self-gating signals in free-breathing three-dimensional cardiac cine magnetic resonance imaging

Conventional multiple breath-hold two-dimensional(2D) balanced steady-state free precession(SSFP) presents many difficulties in cardiac cine magnetic resonance imaging(MRI). Recently, a self-gated free-breathing three-dimensional(3D) SSFP technique has been proposed as an alternative in many studies. However, the accuracy and effectiveness of selfgating signals have been barely studied before. Since self-gating signals are crucially important in image reconstruction, a systematic study of self-gating signals and comparison with external monitored signals are needed.Previously developed self-gated free-breathing 3D SSFP techniques are used on twenty-eight healthy volunteers. Both electrocardiographic(ECG) and respiratory bellow signals are also acquired during the scan as external signals. Self-gating signal and external signal are compared by trigger and gating window. Gating window is proposed to evaluate the accuracy and effectiveness of respiratory self-gating signal. Relative deviation of the trigger and root-mean-square-deviation of the cycle duration are calculated. A two-tailed paired t-test is used to identify the difference between self-gating and external signals. A Wilcoxon signed rank test is used to identify the difference between peak and valley self-gating triggers.The results demonstrate an excellent correlation(P = 0, R 0.99) between self-gating and external triggers. Wilcoxon signed rank test shows that there is no significant difference between peak and valley self-gating triggers for both cardiac(H = 0, P 0.10) and respiratory(H = 0, P 0.44) motions. The difference between self-gating and externally monitored signals is not significant(two-tailed paired-sample t-test: H = 0, P 0.90).The self-gating signals could demonstrate cardiac and respiratory motion accurately and effectively as ECG and respiratory bellow. The difference between the two methods is not significant and can be explained. Furthermore, few ECG trigger errors appear in some subjects while these errors are not found in self-gating signals.