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Relationship Between the Contrast Effects of Raw Data Projection Images from Three-Dimensional Digital Subtraction Angiography and the Optimal Volume Rendering Parameters

机译:三维数字减影血管造影原始数据投影图像的对比度效果与最佳体绘制参数之间的关系

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摘要

Volume rendering (VR) is a technique commonly used for the reconstruction of three-dimensional (3D) digital subtraction angiography (DSA) images, and the rendering parameters greatly affect the characteristics of the 3D image. This study aimed to test whether the optimal VR parameters for 3D DSA could be estimated from the contrast effects in rotational two-dimensional (2D) DSA images acquired using 3D DSA. Simulated blood vessels filled with various concentrations of contrast medium were scanned, and the 3D DSA data sets were reconstructed. The syngo AX vessel analysis software that was able to analyze 3D DSA VR image was used for objective measures. Raw data projection images of the 3D DSA data sets in which the mean diameter was calculated as a true value by the software at nine different thresholds for vessel segmentation were selected. In each image set, five images of all 133 rotational 2D DSA images were selected, and the contrast-enhanced area was extracted using a region-growing algorithm. Mean values and standard deviations of each contrast-enhanced area were calculated, and as the thresholds for vessel segmentation of the software increased by 500 every time, significant differences were observed in the mean values (P < 0.01). This optimal threshold can be applied to the window settings of the VR technique. Therefore, the optimal VR parameters for 3D DSA may be determined by analyzing the contrast effects of the raw data projection images, and user-dependent over- and underestimations of 3D DSA VR images also may be prevented.
机译:体积渲染(VR)是通常用于重建三维(3D)数字减影血管造影(DSA)图像的技术,并且渲染参数极大地影响3D图像的特性。这项研究旨在测试是否可以从使用3D DSA采集的旋转二维(2D)DSA图像中的对比效果估计3D DSA的最佳VR参数。扫描充满不同浓度造影剂的模拟血管,并重建3D DSA数据集。使用能够分析3D DSA VR图像的syngo AX血管分析软件进行客观测量。选择3D DSA数据集的原始数据投影图像,其中通过软件在9个不同的阈值下将平均直径计算为真实值以进行血管分割。在每个图像集中,选择所有133个旋转2D DSA图像中的五个图像,并使用区域增长算法提取对比度增强区域。计算每个对比度增强区域的平均值和标准差,并且随着每次软件分割血管的阈值增加500,平均值均出现显着差异(P <0.01)。可以将此最佳阈值应用于VR技术的窗口设置。因此,可以通过分析原始数据投影图像的对比度效果来确定用于3D DSA的最佳VR参数,并且还可以防止依赖于用户的3D DSA VR图像过高或过低。

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