Performance Assessment of Texture Reproduction in High-Resolution CT.
Performance Assessment of Texture Reproduction in High-Resolution CT.
复制标题
高分辨率 CT 中纹理再现的性能评估。
DOI：
10.1117/12.2550579
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Stayman,JWebster
中科院分区：
文献类型：
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作者：
Shi,Hui;Gang,GraceJ;Li,Junyuan;Liapi,Eleni;Abbey,Craig;Stayman,JWebster
计算机断层扫描（CT）图像的评估可能是复杂的，由于一些影响系统性能的依赖性。特别地，众所周知，CT中的噪声是对象相关的。随着越来越多地采用基于模型的重建和机器学习方法的处理，这种对象依赖性可以更加明显，并扩展到分辨率和图像纹理。此外，这样的处理通常是固有的非线性的，使得利用空间分辨率的简单测量等的评估复杂化。类似地，CT系统设计中的最新进展已经尝试改善精细分辨率细节-例如，认识到这些趋势，更需要成像评估，即考虑可以放置在拟人化体模内的感兴趣的特定特征，以进行逼真的仿真和评估。在这项工作中，我们设计了一种方法，用于3D打印体模插入使用程序纹理生成高分辨率CT系统的性能评估。纹理的准确表示以前一直是采用基于模型的重建等处理方法的障碍，而纹理可以作为重要的诊断特征（例如，病变的异质性是恶性肿瘤的标志）。我们认为不同的系统再现各种纹理的能力（作为纹理的内在特征尺寸的函数），比较microCT，锥束CT，诊断CT使用正常和高分辨率模式。我们期望这种通用方法将为不同成像系统和处理方法的可重复和可靠评估提供途径。
Assessment of computed tomography (CT) images can be complex due to a number of dependencies that affect system performance. In particular, it is well-known that noise in CT is object-dependent. Such object-dependence can be more pronounced and extend to resolution and image textures with the increasing adoption of model-based reconstruction and processing with machine learning methods. Moreover, such processing is often inherently nonlinear complicating assessments with simple measures of spatial resolution, etc. Similarly, recent advances in CT system design have attempted to improve fine resolution details – e.g., with newer detectors, smaller focal spots, etc. Recognizing these trends, there is a greater need for imaging assessment that are considering specific features of interest that can be placed within an anthropomorphic phantom for realistic emulation and evaluation. In this work, we devise a methodology for 3D-printing phantom inserts using procedural texture generation for evaluation of performance of high-resolution CT systems. Accurate representations of texture have previously been a hindrance to adoption of processing methods like model-based reconstruction, and texture serves as an important diagnostic feature (e.g. heterogeneity of lesions is a marker for malignancy). We consider the ability of different systems to reproduce various textures (as a function of the intrinsic feature sizes of the texture), comparing microCT, cone-beam CT, and diagnostic CT using normal- and high-resolution modes. We expect that this general methodology will provide a pathway for repeatable and robust assessments of different imaging systems and processing methods.