Volume 19, Issue 4

Due to vessel overlap and foreshortening, multiple projections are necessary to adequately evaluate the coronary tree with arteriography. Catheter-based interventions can only be optimally performed when these visualization problems are successfully solved. The traditional method provides multiple selected views in which overlap and foreshortening are subjectively minimized based on two dimensional (2-D) projections. A pair of images acquired from routine angiographic study at arbitrary orientation using a single-plane imaging system were chosen for three-dimensional (3-D) reconstruction. After the arterial segment of interest (e.g., a single coronary stenosis or bifurcation lesion) was selected, a set of gantry angulations minimizing segment foreshortening was calculated. Multiple computer-generated projection images with minimized segment foreshortening were then used to choose views with minimal overlapped vessels relative to the segment of interest. The optimized views could then be utilized to guide subsequent angiographic acquisition and interpretation. Over 800 cases of coronary arterial trees have been reconstructed, in which more than 40 cases were performed in room during cardiac catheterization. The accuracy of 3-D length measurement was confirmed to be within an average root-mean-square (rms) 3.5% error using eight different pairs of angiograms of an intracoronary guidewire of 105-mm length with eight radiopaque markers of 15-mm interdistance. The accuracy of similarity between the additional computer-generated projections versus the actual acquired views was demonstrated with the average rms errors of 3.09 mm and 3.13 mm in 20 LCA and 20 RCA cases, respectively. The projections of the reconstructed patient-specific 3-D coronary tree model can be utilized for planning optimal clinical views: minimal overlap and foreshortening. The assessment of lesion length and diameter narrowing can be optimized in both interventional cases and studies of disease progression and regression.

由于血管重叠和缩短，需要多个投影来充分评估冠状动脉造影图像。只有当这些可视化问题得到成功解决时，基于导管的介入治疗才能最佳地进行。传统方法提供多个选定视图，在这些视图中，基于二维投影主观地最小化重叠和缩短。选择常规血管造影研究中使用单平面成像系统以任意方向获取的一对图像进行三维重建。在选定感兴趣的动脉段（例如，单个冠状动脉狭窄或分叉病变）后，计算一组最小化段缩短的机架角度。然后使用多个计算机生成的投影图像（具有最小化的段缩短）来选择相对于感兴趣段具有最小重叠血管的视图。然后可以利用优化视图来指导后续的血管造影采集和解释。已经重建了超过800例冠状动脉树，其中超过40例在心脏导管插入术期间在手术室中进行。三维长度测量的准确性通过使用八对不同长度的冠状动脉内导丝（105毫米，8个不透射线标记，间隔15毫米）的血管造影图得到确认，平均均方根误差为3.5%。附加计算机生成投影与实际获取视图之间的相似性准确性通过20例左冠状动脉和20例右冠状动脉病例的平均均方根误差分别为3.09毫米和3.13毫米得到证明。重建的患者特异性三维冠状动脉树模型的投影可用于规划最佳临床视图：最小重叠和缩短。病变长度和直径狭窄的评估可以在介入病例以及疾病进展和退化的研究中得到优化。

A method is presented which aids the clinician in obtaining quantitative measures and a three-dimensional (3-D) representation of vessels from 3-D angiographic data with a minimum of user interaction. Based on two user defined starting points, an iterative procedure tracks the central vessel axis. During the tracking process, the minimum diameter and a surface rendering of the vessels are computed...

提出了一种方法，帮助临床医生以最少的用户交互从三维血管造影数据中获取血管的定量测量和三维表示。基于两个用户定义的起始点，迭代过程追踪血管中心轴线。在追踪过程中，计算血管的最小直径并生成表面渲染。

Gridding reconstruction is a method to reconstruct data onto a Cartesian grid from a set of nonuniformly sampled measurements. This method is appreciated for being robust and computationally fast. However, it lacks solid analysis and design tools to quantify or minimize the reconstruction error. Least squares reconstruction (LSR), on the other hand, is another method which is optimal in the sense ...

网格重建是一种从一组非均匀采样测量数据重建到笛卡尔网格的方法。该方法因其鲁棒性和计算速度快而受到赞赏。然而，它缺乏量化和最小化重建误差的可靠分析和设计工具。另一方面，最小二乘重建（LSR）是另一种在某种意义上最优的方法...

Researchers have shown increasing interest in block-iterative image reconstruction algorithms due to the computational and modeling advantages they provide. Although their convergence properties have been well documented, little is known about how they behave in the presence of noise. In this work, the authors fully characterize the ensemble statistical properties of the rescaled block-iterative e...

研究人员对块迭代图像重建算法的兴趣日益增加，因为它们提供了计算和建模上的优势。尽管它们的收敛性已被充分记录，但它们在噪声存在下的表现却知之甚少。在这项工作中，作者全面描述了重缩放块迭代的集合统计特性...

In medical imaging it is common to reconstruct dense motion estimates, from sparse measurements of that motion, using some form of elastic spline (thin-plate spline, snakes and other deformable models, etc.). Usually the elastic spline uses only bending energy (second-order smoothness constraint) or stretching energy (first-order smoothness constraint), or a combination of the two. These elastic s...

在医学成像中，通常使用某种形式的弹性样条（薄板样条、蛇模型和其他可变形模型等）从稀疏的运动测量中重建稠密的运动估计。通常弹性样条只使用弯曲能量（二阶平滑约束）或拉伸能量（一阶平滑约束），或两者的组合。这些弹性...

Interior-point methods have been successfully applied to a wide variety of linear and nonlinear programming applications. This paper presents a class of algorithms, based on path-following interior-point methodology, for performing regularized maximum-likelihood (ML) reconstructions on three-dimensional (3-D) emission tomography data. The algorithms solve a sequence of subproblems that converge to...

内点方法已成功应用于各种线性和非线性规划问题。本文提出了一类基于路径跟踪内点方法的算法，用于在三维发射断层扫描数据上执行正则化最大似然重建。这些算法求解一系列子问题，这些子问题收敛到...

For an objective interpretation of cerebral metabolic pattern to find epileptogenic zones in patients with temporal lobe epilepsy (TLE), the authors developed a computer-aided classifier using an artificial neural network (ANN). They studied 261 epilepsy patients diagnosed as no abnormal findings (NA, n=64), left TLE (n=116), or right TLE (n=81) on interictal brain F-18-fluorodeoxyglucose positron...

为了客观解释脑代谢模式以发现颞叶癫痫（TLE）患者的致痫区，作者开发了一种使用人工神经网络（ANN）的计算机辅助分类器。他们研究了261例癫痫患者，其中间期脑F-18-氟脱氧葡萄糖正电子发射断层扫描（PET）显示无异常发现（NA，n=64）、左侧TLE（n=116）或右侧TLE（n=81）。

Presents a method for approximating constrained maximum entropy (ME) reconstructions of SPECT data with modifications to a block-iterative maximum a posteriori (MAP) algorithm. Maximum likelihood (ML)-based reconstruction algorithms require some form of noise smoothing. Constrained ME provides a more formal method of noise smoothing without requiring the user to select parameters. In the context o...

提出了一种方法，通过对块迭代最大后验（MAP）算法进行修改，来近似SPECT数据的约束最大熵（ME）重建。基于最大似然（ML）的重建算法需要某种形式的噪声平滑。约束ME提供了一种更正式的噪声平滑方法，无需用户选择参数。在...的背景下