X-ray beam equalization: feasibility and performance of an automated prototype system in a phantom and swine.

X-ray beam equalization: feasibility and performance of an automated prototype system in a phantom and swine.
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X 射线束均衡:模型和猪中自动化原型系统的可行性和性能。

DOI:
10.1148/radiol.2213010183
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发表时间:
2001
期刊:
Radiology.
影响因子:
--
通讯作者:
Wang,F
Wang,F
中科院分区:
--
文献类型:
--
作者:
Molloi,S;VanDrie,A;Wang,F

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目的:探讨一个自动化实施的光束均衡技术的可行性,并评估实验性能的原型system.MATERIALS和METHODS:X射线光束均衡涉及的过程中,低剂量的图像采集,衰减器厚度计算,掩模生成,掩模定位,均衡的图像采集,掩模整形。整个均衡过程在大约7秒内完成。利用仿人体模和猪动物模型对均衡后的图像进行了定性和定量评价。评估了总体图像质量,以评估动脉分支和其他解剖结构的可视化能力。通过将图像分割成8 × 8的方形区域矩阵来定量评估均衡化水平。结果:来自人形体模和猪动物研究的均衡化和非均衡化图像的均方根方差之比分别为0.49和0.59。此外,图像的定性评估显示,在幻影和动物study.CONCLUSION光束均衡后,图像质量和动脉分支的可视化有了很大的改善:自动区域光束均衡是可行的,提高了图像质量在以前的欠穿透区域的图像。
PURPOSE:To investigate the feasibility of an automated implementation of a beam equalization technique and to evaluate the experimental performance of the prototype system.MATERIALS AND METHODS:X-ray beam equalization involved the process of low-dose image acquisition, attenuator thickness calculation, mask generation, mask positioning, equalized image acquisition, and mask reshaping. The entire equalization process was performed in approximately 7 seconds. The equalized images were assessed both qualitatively and quantitatively by using a humanoid phantom and a swine animal model. The general image quality was assessed for the ability to visualize arterial branches and other anatomic structures. The level of equalization was quantitatively assessed by segmenting the images into an 8 × 8 matrix of square regions.RESULTS:The ratio of the root-mean-squared variance for the equalized and unequalized images from humanoid phantom and swine animal studies was 0.49 and 0.59, respectively. Furthermore, qualitative assessment of the images showed substantial improvement in image quality and visualization of arterial branches after beam equalization in phantom and animal studies.CONCLUSION:Automated area beam equalization is feasible and improves image quality in previously underpenetrated regions of the image.
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