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Image-quality figure evaluator based on contrast-detail phantom in radiography

机译:基于造影细节体模的图像质量人物评价器

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Background: In radiology, it is significantly important to produce adequate diagnostic information while minimally affecting the patient with the lowest amount of dose. A contrast-detail phantom is generally used to study the quality of image and the amount of radiation dose for digital X-ray imaging systems. To evaluate the quality of a phantom image, radiologists are traditionally required to manually indicate the location of the holes in each square in the phantom image. Then, the image quality figure (IQF) of the image can be evaluated. However, evaluation by the human eye is subjective as well as time-consuming, and it differs from person to person. Methods: In this paper, an image processing-based IQF evaluator is proposed to automatically measure the quality of a phantom image. Nine phantom images, each consisting of 2382×2212 pixels, were used as test images and were provided by Taichung Hospital, Department of Health, Executive Yuan, Taiwan, Republic of China. The IP-IQF evaluator separates the phantom image into squares and then stretches the contrast of each square to the range 0-255. After that, it splits each square into 3×3 equal-sized regions, and recognizes the pattern of the square based on the features computed by mean-difference gradient operation and run length enhancer. Furthermore, a genetic algorithm-based parameter values-detecting algorithm is presented to compute the optimal values of the parameters used in the IP-IQF evaluator. Results: The experimental results demonstrate that CoCIQ and the IP-IQF evaluator can efficiently measure the IQF of a phantom image. The IP-IQF evaluator is more effective than a radiologist and CoCIQ in evaluating the IQF of a phantom image. Conclusions: The proposed IQF evaluator is more sensitive than not only the observation of radiologists but also the computer program CoCIQ. Moreover, a genetic algorithm is provided to compute the most suitable values of the parameters used in the IQF evaluator.
机译:背景:在放射学中,产生足够的诊断信息,同时以最小的剂量将对患者的影响降到最低,这一点非常重要。对比细节模型通常用于研究数字X射线成像系统的图像质量和辐射剂量。为了评估体模图像的质量,传统上要求放射科医生手动指示体模图像中每个正方形中的孔的位置。然后,可以评估图像的图像质量指数(IQF)。但是,人眼评估既主观又费时,而且因人而异。方法:在本文中,提出了一种基于图像处理的IQF评估器来自动测量幻像图像的质量。九张幻像图像(每个幻像图像由2382×2212像素组成)用作测试图像,由中华民国台湾行政院卫生署台中医院提供。 IP-IQF评估程序将幻像图像分成正方形,然后将每个正方形的对比度扩展到0-255的范围。此后,它将每个正方形划分为3×3相等大小的区域,并基于通过均值差梯度运算和游程长度增强器计算出的特征来识别正方形的图案。此外,提出了一种基于遗传算法的参数值检测算法,以计算IP-IQF评估器中使用的参数的最佳值。结果:实验结果表明,CoCIQ和IP-IQF评估程序可以有效地测量幻像的IQF。 IP-IQF评估器在评估幻像的IQF方面比放射科医生和CoCIQ更有效。结论:所提出的IQF评估器不仅比放射科医生的观察更为敏感,而且比计算机程序CoCIQ更敏感。此外,提供了一种遗传算法来计算IQF评估器中使用的参数的最合适值。

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