Graduate School of Medical Sciences, Kanazawa University, Ishikawa, 920-0942, Japan.
College of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Ishikawa, 920-0942, Japan.
Phys Med Biol. 2024 Mar 26;69(7). doi: 10.1088/1361-6560/ad3119.
The purpose of this study is to propose a novel blurring correction method that enables accurate quantitative analysis of the object edge when using energy-resolving photon counting detectors (ERPCDs). Although the ERPCDs have the ability to generate various quantitative analysis techniques, such as the derivations of effective atomic number () and bone mineral density values, at the object edge in these quantitative images, accurate quantitative information cannot be obtained. This is because image blurring prevents the gathering of accurate primary x-ray attenuation information.We developed the following procedure for blurring correction. A 5 × 5 pixels masking region was set as the processing area, and the pixels affected by blurring were extracted from the analysis of pixel value distribution. The blurred pixel values were then corrected to the proper values estimated by analyzing minimum and/or maximum values in the set mask area. The suitability of our correction method was verified by a simulation study and an experiment using a prototype ERPCD.. Whenimage of aluminum objects (= 13) were analyzed without applying our correction method, regardless of raw data or correction data applying a conventional edge enhancement method, the propervalues could not be derived for the object edge. In contrast, when applying our correction method, 82% of pixels affected by blurring were corrected and the propervalues were calculated for those pixels. As a result of investigating the applicability limits of our method through simulation, it was proven that it works effectively for objects with 4 × 4 pixels or more.. Our method is effective in correcting image blurring when the quantitative image is calculated based on multiple images. It will become an in-demand technology for putting a quantitative diagnosis into actual medical examinations.
本研究旨在提出一种新的模糊校正方法，该方法可在使用能量分辨光子计数探测器（ERPCD）时准确地对物体边缘进行定量分析。虽然 ERPCD 具有生成各种定量分析技术的能力，例如有效原子数（Zeff）和骨矿物质密度值的推导，但在这些定量图像中的物体边缘，无法获得准确的定量信息。这是因为图像模糊会阻止准确收集原始 X 射线衰减信息。我们开发了以下模糊校正程序。设置一个 5×5 像素的掩蔽区域作为处理区域，并从像素值分布分析中提取受模糊影响的像素。然后，将模糊像素值校正为通过分析设置掩模区域中的最小和/或最大值来估计的适当值。通过使用原型 ERPCD 进行的模拟研究和实验验证了我们的校正方法的适用性。当未应用我们的校正方法分析铝物体的图像（Zeff=13）时，无论原始数据还是应用常规边缘增强方法的校正数据，都无法为物体边缘推导出适当的值。相比之下，当应用我们的校正方法时，82%的受模糊影响的像素被校正，并且对这些像素计算了适当的值。通过模拟研究调查我们方法的适用性限制，证明它对具有 4×4 个像素或更多像素的物体有效。当基于多个图像计算定量图像时，我们的方法在纠正图像模糊方面非常有效。它将成为实际医学检查中进行定量诊断的一项急需的技术。
