Filtered backprojection algorithm can outperform iterative maximum likelihood expectation‐maximization algorithm

The iterative maximum‐likelihood expectation‐maximization (ML‐EM) algorithm is an excellent algorithm for image reconstruction and usually provides better images than the filtered backprojection (FBP) algorithm. However, a windowed FBP algorithm can outperform the ML‐EM in certain occasions, when the least‐squared difference from the true image, that is, the least‐squared error (LSE), is used as the comparison criterion. Computer simulations were carried out for the two algorithms. For a given data set the best reconstruction (compared to the true image) from each algorithm was first obtained, and the two reconstructions are compared. The stopping iteration number of the ML‐EM algorithm and the parameters of the windowed FBP algorithm were determined, so that they produced an image that was closest to the true image. However, to use the LSE criterion to compare algorithms, one must know the true image. How to select the optimal parameters when the true image is unknown is a practical open problem. For noisy Poisson projections, computer simulation results indicate that the ML‐EM images are better than the regular FBP images, and the windowed FBP algorithm images are better than the ML‐EM images. For the noiseless projections, the FBP algorithms outperform the ML‐EM algorithm. The computer simulations reveal that the windowed FBP algorithm can provide a reconstruction that is closer to the true image than the ML‐EM algorithm. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 114–120, 2012     

A Time－space Domain Backprojection Method for Ray Inversion in Layered Medium

ＡＴｉｍｅ－ｓｐａｃｅＤｏｍａｉｎＢａｃｋｐｒｏｊｅｃｔｉｏｎＭｅｔｈｏｄｆｏｒＲａｙＩｎｖｅｒｓｉｏｎｉｎＬａｙｅｒｅｄＭｅｄｉｕｍＭＡＸｉｎｒｕｉＴＡＯＬｉａｎｇＨＵＡＮＧＷｅｎｈｕ（马兴瑞，陶良，黄文虎）（Ｄｅｐｔ．ｏｆＡｓｔｒｏｎａｕｔｉｃｓ...     

一种改进的窄带算法在彩色序列图像人脸跟踪中的应用

该文提出了一种基于几何主动轮廓模型的人脸跟踪方法.通过直方图反向投影,使人脸区域表现为一个一致性区域与背景相区别.研究了一种改进的窄带算法实现曲线演化:以等间隔分布的节点表示运动曲线,只在这些节点上计算Level set函数的变化值,窄带区内其余点的Level set值的更新通过插值和查表的方法实现;根据节点的局部图像信息决定节点的运动方向和时间步长值.实验表明该算法能在满足一定精度的前提下,快速地对运动人脸进行跟踪.     

Fast Feldkamp reconstruction based on focus of attention and distributed computing

The Feldkamp algorithm is widely accepted as a practical conebeam reconstruction method for three‐dimensional x‐ray computed tomography. We introduce focus of attention, an effective and simple to implement datadriven preprocessing scheme, for identifying a convex subset of voxels that include all those relevant to the object under study. By concentrating on this subset of voxels during reconstruction, we reduce the computational demands of the Feldkamp algorithm correspondingly. To achieve further speed‐up, all computations are distributed across a cluster of inexpensive, dual‐processor PCs. We present experimental work based on mouse data obtained from the MicroCAT which is a high‐resolution x‐ray computed tomography system for small animal imaging. This work shows that focus of attention can cut the overall computation time in half without affecting the image quality. The method is general by nature and can easily be adapted to apply to other geometries and modalities as well as to iterative reconstruction algorithms. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 12, 229–234, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10027     

基于小波变换的滤波反投影算法

滤波反投影算法是Ｒａｄｏｎ 逆变换最常用的一种数值计算方法,在ＣＴ技术和信号处理中得到了广泛的应用。本文把小波变换应用于滤波反投影算法中,给出了一种用小波变换对投影数据作滤波处理的方法,这种方法与常规方法比较,具有精度高,抗噪能力强,参数易于选取等优点。文中给出了模型和实际地震资料处理实例,证明了该方法的有效性。     

Error analysis of tomographic filters II: results

The convolution backprojection algorithm (CBP) has been studied from the point-of-view of the already published error formula which relates the error in reconstructions, under certain ideal conditions, to the Fourier-space derivatives of the filter functions employed in CBP. The results, for simulated images representing a damaged nuclear reactor fuel assembly and a cross-section of human brain, indicate that the error pattern obtained is in concurrence with the theory. Experimental results for a pixel size of 20 μm are also included.     

三维 CT 在锥角增大时对重建图像质量的影响

通过分析圆柱状物体在不同锥角时对重建图像质量的影响 ,从而得出传统三维 CT适宜于小锥角(大约 6°)情况时的重建的结论     

基于多状态分层模型的有表情人脸配准

将人脸表情变化范围离散化表示为多状态部件模型,以便描述人脸非线性变化。引入多方向局部梯度信息,建立反投影概率图来改善原始灰度图像的外观模式表达,基于级联的卷积神经网络实现渐进分层的人脸配准。根据整脸和不同区域的图像实现人脸形状初始化,并判断当前部件状态。根据正确状态的人脸模型回归人脸形状参数,完成最终的精细配准。与其他几种常用算法在数据库上进行了定量比较,结果表明该算法改善了表情变化剧烈时人脸配准的效果,在计算量相当的情况下,正确率和处理速度等方面都达到很好的性能,具有明显的实用价值。     

一种基于Grengeat公式的锥束CT重建算法研究

基于单圆轨迹的Feldkamp(FDK)重建算法只有在小锥角条件下才能取得较好重建效果。随着锥角增大,图像质量迅速下降。因此在实际应用中受到一定限制。在分析了物体Radon数据与单圆扫描获得的Radon数据间的关系后,结合空间可变滤波反投影重建算法(SV_FBP),提出了一种基于Grengeat公式的叠加算法。该重建算法由两部分重建结果叠加而成,第1部分结果首先采用FDK算法通过对单圆扫描的投影数据进行重建来获得;然后采用外推方法获得缺失的数据,并利用SV_FBP进行重建得到第2部分结果;最后将两部分结果进行叠加。实验结果表明,该算法不仅有效地抑制了FDK算法重建的伪影,而且使锥角的使用范围比FDK算法提高了3~4倍。这种新的叠加重建算法在大长物体的重建中,具有重要的理论和应用价值。     

一种局部CT图像重建算法研究

CT作为一种无创检查设备在医学领域得到广泛的应用,但是受重建方法的限制,它通常只能对相对静止的器官进行扫描断层成像,而对运动物体或器官的成像能力较差,通常会存在运动伪影.克服运动伪影的根本途径就是减少数据采集的时间,这可以通过减少采集范围来实现.中间函数重建算法是一种基于傅里叶空间的重建算法,该算法可以选择感兴趣的部位(ROI)进行局部图像重建,减少数据采集的时间,因此可以使用该算法改善临床上运动物体的扫描成像.