Assessment of Boundary Discrimination Performance in a Printed Phantom.
Assessment of Boundary Discrimination Performance in a Printed Phantom.
复制标题
印刷体模的边界辨别性能评估。
DOI：
10.1117/12.2612622
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Stayman,JWebster
中科院分区：
文献类型：
--
作者：
Abbey,CraigK;Li,Junyuan;Gang,GraceJ;Stayman,JWebster
打印模体作为检查基于任务的X射线成像系统的图像质量的工具具有巨大的潜力。它们能够产生在衰减系数可调的材料中渲染的复杂形状，从而使物理成像系统评估任务的设计具有更高的灵活性。我们调查了在一个精细的“边界辨别”任务中的表现，在这个任务中，一个清晰可见的“病变”的边缘的精细特征被用来将该病变分类为恶性或良性。这些任务之所以吸引人，是因为它们与临床任务相关，而且它们通常强调相对于更常见的病变检测任务更高的空间频率。使用包含不同厚度的圆柱壳的3D打印体模来生成边缘轮廓不同的病变轮廓。这是为了接近边缘模糊的病变，这些病变在临床上与恶性肿瘤有关。体模的壁厚从0.4 mm到0.8 mm不等，这允许通过选择不同的厚度来代表恶性和良性病变来改变任务难度。模型被浸泡在装满水和磷酸钾的浴缸中，以接近衰减的背景，并在台式锥束CT扫描仪上重复成像。经过图像数据的准备(重建、ROI选择、亚像素配准)，我们发现病变轮廓的平均频率为0.11cyc/mm。代表辨别任务的病变-差异轮廓的平均频率大约是识别任务的6倍。模型观察者在这些任务中也显示出适当的剂量表现。
Printed phantoms hold great potential as a tool for examining task-based image quality of x-ray imaging systems. Their ability to produce complex shapes rendered in materials with adjustable attenuation coefficients allows a new level of flexibility in the design of tasks for the evaluation of physical imaging systems. We investigate performance in a fine “boundary discrimination” task in which fine features at the margin of a clearly visible “lesion” are used to classify the lesion as malignant or benign. These tasks are appealing because of their relevance to clinical tasks, and because they typically emphasize higher spatial frequencies relative to more common lesion detection tasks. A 3D printed phantom containing cylindrical shells of varying thickness was used to generate lesions profiles that differed in their edge profiles. This was intended to approximate lesions with indistinct margins that are clinically associated with malignancy. Wall thickness in the phantom ranged from 0.4mm to 0.8mm, which allows for task difficulty to be varied by choosing different thicknesses to represent malignant and benign lesions. The phantom was immersed in a tub filled with water and potassium phosphate to approximate the attenuating background, and imaged repeatedly on a benchtop cone-beam CT scanner. After preparing the image data (reconstruction, ROI Selection, sub-pixel registration), we find that the mean frequency of the lesion profile is 0.11 cyc/mm. The mean frequency of the lesion-difference profile, representative of the discrimination task, is approximately 6 times larger. Model observers show appropriate dose performance in these tasks as well.