旋转扫描超声心脏图像的中轴匹配与图像插值

研究旋转扫描超声医学图像多维重建中图像中轴匹配方法和插值算法。首先 ,根据图像中轴的特征点分析其时域曲线 ,实现中轴的轴向匹配 ;相似矩阵用来寻找两幅图像中轴附近匹配的像素线。自相关函数和 Fouri-er谱用来对图像中轴的匹配进行评价。其次 ,针对旋转扫描原始图像空间分布的特殊性 ,提出了分区插值法。实验结果表明 :我们提出的图像中轴匹配方法切实可行 ,插值算法快速、精确 ,基于匹配的插值算法可大大改善重建质量     

血管造影图像序列中冠状动脉的三维运动估计

提出了由两个角度的单面血管造影图像序列估计冠状动脉骨架树三维运动的算法。首先对冠状动脉造影图像序列进行二维预处理和二维运动估计。然后根据冠脉造影系统的透视投影模型得到两幅不同角度的造影图像之间的几何变换关系，以及空间点三维坐标的计算方法。最后，在对整个图像序列进行分析的过程中，将三维运动估计与重建结合起来，得到各骨架点的三维运动向量。采用临床得到的冠状动脉造影图像序列对算法进行了验证，并分析了误差源。     

用于面诊的人脸全景图像拼接算法

采用一种基于人脸特征的柱面投影方法,将人的头部近似看做一个圆柱体,有效地解决了在采集过程中因面部角度所引起的视觉不一致性;利用SIFT特征匹配算法提取两幅图像的特征向量,并通过RANSAC匹配优化算法消除错误的匹配,实现图像的配准;接着采用渐入渐出的融合算法,使图像间实现平滑的过渡,消除拼接缝隙。实验结果表明,本研究使用的算法能够快速、有效地生成人脸全景图像,为后续中医面诊奠定了基础。     

基于非刚体配准的体数据插值重建方法

三维图像的处理和操作需要将一般的断层序列插值成为具有各坐标轴一致的分辨率的体数据，而目前最常用的线性插值方法在层间距较大时会导致图像边缘模糊和出现伪影。Penney根据现有的非刚体匹配方法，提出了利用图像形变场数据的插值算法，大大提高了层间插值的质量。本文对Penney提出的算法进行了两方面的改进，在配准过程中用简单的单射性约束取代了复杂的平滑性约束，用邻域平均算法替代Penney使用的最邻近直线插值方法，并将新算法的实验结果与原算法、线性插值进行了对比。新算法在保持高质量插值的前提下提高了计算速度。该算法可以应用于精度要求比较高的体数据插值重建过程。     

基于SIFT特征和近似最近邻算法的医学CT图像检索

针对医学X线计算机断层(Computed Tomography,CT)图像,提出了一种基于尺度不变特征变换(Scale InvariantFeature Transform,SIFT)特征和近似最近邻算法的检索方法。首先通过SIFT算法得到图像的特征点和相应的特征向量,再采用近似最近邻算法进行SIFT特征向量的匹配搜索,得到数据库中与参考图像最相似的图像序列。实验结果表明,该法能检索到与目标图像细节相符的结果,大大提高了检索速度。与传统的基于纹理的检索方法相比,查准率和检索结果与目标图像的相似程度方面更佳,符合医学CT图像检索的要求。     

平行束单光子发射成像的定量解析重建

单光子发射断层成像技术在心血管及脑功能疾病的诊断上具有重要的临床意义。本研究以Kunyansky及以前的研究工作为基础，针对平行束探测模式，推导及建立了有效的解析重建算法，可对噪声、散射、衰减及探测器响应进行同时补偿，用于获取SPECT定量快速成像。数字及Monte Carlo仿真实验表明，所提出的定量解析重建算法是可行的，它极大地改善了重建图像的对比度及分辨率，基本消除了图像中的伪迹。该算法在达到迭代算法精度的同时，计算量却大为降低，与常规滤波反投影重建法近似。     

血管树拓扑描述及匹配方法的研究

血管树的拓扑描述及匹配是由二维血管造影图像重建三维血管树的关键步骤,我们采用二叉树描述二维血管骨架树,提出“结点权值”和“相似结点”的概念,很好地描述了血管树的拓扑结构。同时根据二叉树的前序遍历结果匹配血管段,有效地提高了匹配的速度和准确度。     

一种连续轮廓组的多边形逼近与匹配算法

提出一种适合于连续医学图像序列的轮廓匹配算法.基于笛卡尔坐标空间,首先对医学图像轮廓曲线进行离散化,运用多边形逼近算法提取点数最多轮廓的特征点,然后依据多边形相似度来提取剩余轮廓的特征多边形,使得相邻轮廓之间达到最好的匹配.实验结果表明,该算法可以得到很好的匹配效果.     

排除模板迭代算法在数字减影血管造影中的应用

本文基于ＤＳＡ图象中由于选影剂的影响存在灰度差别的特点，提出了一种新的匹配算法－－排除板迭代算法，成功地实现了ＤＳＡ图象中的运动伪象和灰度伪象的校正。在我们的算法中利用排除模板将存在显著灰度差别的ＤＳＡ序列图像转换为可以 利用古典匹配算法的序列图象，而且在用排除模板进行匹配的过程中，逐次迭代，直至最佳匹配状态。整个算法实现了全自动，且匹配速度快，搜索范围大，精度可达１个象素点。实验结果表明，此方法     

一种非规则三维实体重建算法及其在医学骨图像分析中的应用

本研究提出了一种由断层面切片进行三维实体表面重建的改进方法 ,它将划分曲面、立体建模与传统的划分三角形法和局部特征匹配相结合。该方法通过在划分三角形系统中加入曲线匹配过程 ,以生成物体的垂直轮廓线 ,从而改善了Tagare等人[1] 提出的三角平面建模技术。三维物体的立体建模是通过轮廓网格产生的。实验结果表明 ,我们的建模系统比传统的划分三角形方法可以生成更精确、细致的图像 ,同时能以精细的分辨率观察三维几何特征和进行更方便、准确的三维测量     

基于分层策略的凝胶图像间蛋白点匹配算法

凝胶图像间蛋白点比对分析是蛋白质组学研究的重要方法,针对凝胶图像间蛋白点人工比对工作量大和易出错等问题,提出一种基于分层策略的凝胶图像间蛋白点自动匹配算法。首先将每张凝胶图像中的蛋白点按不同灰度等级划分到对应层级中;然后根据蛋白点的灰度相关性,采用归一化互相关法对各层级蛋白点进行粗匹配;最后以粗匹配蛋白点点对作为标记特征点,采用几何相关法和相似性准则,实现蛋白点间的精确匹配。通过对国际凝胶图和Bio-Rad公司测试图等不同图源的凝胶图像进行蛋白点匹配实验,结果表明,该算法具有较高的匹配精度,其匹配误差小于4%,对不同来源和不同图像形变的凝胶图像都具有较好的稳定性。     

Matching and reconstruction of brachytherapy seeds using the Hungarian algorithm (MARSHAL)

Intraoperative dosimetric quality assurance in prostate brachytherapy critically depends on discerning the three-dimensional (3D) locations of implanted seeds. The ability to reconstruct the implanted seeds intraoperatively will allow us to make immediate provisions for dosimetric deviations from the optimal implant plan. A method for seed reconstruction from segmented C-arm fluoroscopy images is proposed. The 3D coordinates of the implanted seeds can be calculated upon resolving the correspondence of seeds in multiple x-ray images. We formalize seed-matching as a combinatorial optimization problem, which has salient features: (a) extensively studied solutions by the computer science community; (b) proof for the nonexistence of any polynomial time exact algorithm; and (c) a practical pseudo-polynomial algorithm that mostly runs in O(N3) time using any number of images. We prove that two images are insufficient to correctly match the seeds, while a third image renders the matching problem to be of nonpolynomial complexity. We utilize the special structure of the problem and propose a pseudopolynomial time algorithm. Using three presegmented images, matching and reconstruction of brachytherapy seeds using the Hungarian algorithm achieved complete matching in simulation experiments; and 98.5% in phantom experiments. 3D reconstruction error for correctly matched seeds has a mean of 0.63 mm, and 0.9 mm for incorrectly matched seeds. The maximum seed reconstruction error in each implant was typically around 1.32 mm. Both on synthetic data and in phantom experiments, matching rate and reconstruction error achieved using presegmented images was found to be sufficient for prostate brachytherapy. The algorithm is extendable to deal with arbitrary number of images without any loss in speed or accuracy. The algorithm is sufficiently generic to provide a practical solution to any correspondence problem, across different imaging modalities and features.     

Three-dimensional knowledge driven reconstruction of coronary trees

A knowledge-driven approach to the three-dimensional reconstruction of coronary artery trees by means of two X-ray projections is proposed. The spatial reconstruction of the tree skeleton is discussed. A binary tree model of the arterial structure and its projections is employed. Consequently, the reconstruction of the three-dimensional tree skeleton is achieved by (a) matching the skeletons of corresponding pairs of vascular segments in the two views and (b) back-projecting the coupled skeleton projections. From a geometrical point of view, the matching problem is, in general, ill-conditioned. For this reason, additional information sources were used. Thus, the matching phase is accomplished by using both the imaging geometry information, as well as anatomical and topological knowledge, about the coronary arteries coded in a rule base. As far as the back-projection phase is concerned, an algorithm was developed based on: (1) the imaging geometry, (2) the bounding of the back-projection error and (3) a contiguity criterion.     

基于改进尺度不变特征变换的手术室多视点图像拼接算法

目的为了提高手术室环境下拼接后全景图像的主观质量,本文提出一种基于改进尺度不变特征变换(scale invariant feature transform,SIFT)的手术室多视点图像拼接算法。方法基于SIFT特征点匹配算法,依据手术室采集设备为平行摄像机且获取的两视点高关注区域重叠较宽泛的特点,提出采用局部加权融合的拼接算法消除拼接重影,并在局部加权融合算法下,对参与图像空间变换的特征点在垂直方向增加约束,筛选出正确匹配特征点对以消除拼接折痕。结果此算法解决了手术室拼接图像中手术衣的袖子、手术剪和手套的重影及治疗巾位置拼缝不对齐的问题,即消除了术野高关注度下的拼接重影及误匹配带来的拼接折痕,保证了两幅图像拼缝后的平滑过渡。结论基于改进SIFT特征点匹配的算法获得了较好的主观手术画面的拼接质量。     

Adaptive Voxel Matching for Temporal CT Subtraction

Temporal subtraction (TS) technique calculates a subtraction image between a pair of registered images acquired from the same patient at different times. Previous studies have shown that TS is effective for visualizing pathological changes over time; therefore, TS should be a useful tool for radiologists. However, artifacts caused by partial volume effects degrade the quality of thick-slice subtraction images, even with accurate image registration. Here, we propose a subtraction method for reducing artifacts in thick-slice images and discuss its implementation in high-speed processing. The proposed method is based on voxel matching, which reduces artifacts by considering gaps in discretized positions of two images in subtraction calculations. There are two different features between the proposed method and conventional voxel matching: (1) the size of a searching region to reduce artifacts is determined based on discretized position gaps between images and (2) the searching region is set on both images for symmetrical subtraction. The proposed method is implemented by adopting an accelerated subtraction calculation method that exploit the nature of liner interpolation for calculating the signal value at a point among discretized positions. We quantitatively evaluated the proposed method using synthetic data and qualitatively using clinical data interpreted by radiologists. The evaluation showed that the proposed method was superior to conventional methods. Moreover, the processing speed using the proposed method was almost unchanged from that of the conventional methods. The results indicate that the proposed method can improve the quality of subtraction images acquired from thick-slice images.     

融合块匹配和插值法的膈肌应变估计及分析

为了准确评估膈肌收缩功能，提出一种融合块匹配法和插值法的膈肌运动位移和应变估计方法。首先利用基于归一化互相关的块匹配法结合膈肌生理约束特性估计出膈肌感兴趣区域的互相关函数，对膈肌运动的整数位移进行估计；然后利用9点抛物线插值算法对互相关函数进行插值处理，进一步计算膈肌感兴趣区域二维亚像素位移；接下来根据估计出的位移计算应变；最后利用反追踪的思想选取最佳窗口的大小，以降低位移追踪误差。按照上述方法，分别针对吸气相超声膈肌全序列图像以及含吸气开始和吸气结束的首尾两张膈肌图像进行追踪，观察不同大小感兴趣区域窗口设置对膈肌运动位移和应变估计的影响。实验结果表明块匹配算法的窗口大小选择中，5×10和10×15窗口存在匹配错误，15×20、20×25、25×30、30×35窗口追踪得到的水平位移和竖直位移均无显著差异，而固定窗口大小为25×30最佳；选择使用全序列图像和首尾两张图像对膈肌全局应变计算不存在显著差异。     

Application of Kohonen network for automatic point correspondence in 2D medical images

In this paper, a generalized application of Kohonen Network for automatic point correspondence of unimodal medical images is presented. Given a pair of two-dimensional medical images of the same anatomical region and a set of interest points in one of the images, the algorithm detects effectively the set of corresponding points in the second image, by exploiting the properties of the Kohonen self organizing maps (SOMs) and embedding them in a stochastic optimization framework. The correspondences are established by determining the parameters of local transformations that map the interest points of the first image to their corresponding points in the second image. The parameters of each transformation are computed in an iterative way, using a modification of the competitive learning, as implemented by SOMs. The proposed algorithm was tested on medical imaging data from three different modalities (CT, MR and red-free retinal images) subject to known and unknown transformations. The quantitative results in all cases exhibited sub-pixel accuracy. The algorithm also proved to work efficiently in the case of noise corrupted data. Finally, in comparison to a previously published algorithm that was also based on SOMs, as well as two widely used techniques for detection of point correspondences (template matching and iterative closest point), the proposed algorithm exhibits an improved performance in terms of accuracy and robustness.     

结合区域信息的分段活动轮廓模型

提出了一种结合区域信息的分段活动轮廓模型，利用边缘信息迅速找到对象的大体轮廓，然后结合区域统计信息使模型精确收敛到对象边缘。分段的层次化变形有效的利用了图像的全局和局部信息，使用仿射变换使模型的局部以同一种变换方式变形，提高模型对噪声和伪边缘的鲁棒性，同时保持模型轮廓形状的一致性。在精确匹配阶段利用区域统计信息重新定义模型的外部能量，采用自适应的搜索区域确定方法，提高了算法的效率和进入凹边缘的能力。试验表明本模型运算速度快，抗噪声和避免陷入局部极小值的能力较强，有较好的分割效果。