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临床前锥形束微CT中与重建无关的分辨率极限:闭式分析

Reconstruction-Independent Resolution Limits in Preclinical Cone-Beam Micro-CT: A Closed-Form Analysis

Falk L. Wiegmann, Nancy L. Ford

arXiv 2607.12998首次发表:更新:

AI 中文总结

研究临床前锥形束微CT中与重建无关的分辨率极限,推导光子噪声和角采样极限的闭式表达式,组合成有效分辨率图,给出扫描设计最优值及预算分配规则,并用实例和计算器展示相关内容。

AI 中文摘要

临床前锥形束微CT的空间分辨率受两个与重建无关的极限限制。一个是基于投影域信号精确已知、背景精确已知(SKE/BKE)理想观察者和罗斯准则的光子噪声极限,另一个是克劳瑟准则的角采样极限。光子噪声极限是输入数据的属性,适用于任何重建算法。角采样极限适用于不注入信号先验的经典解析和迭代重建。我们推导了均匀背景中圆形特征的两个极限的闭式表达式,包括离轴扇形束扩展,并将它们组合成空间变化的有效分辨率图。组合极限产生闭式扫描设计最优值。最大最坏情况空间频率与每个探测器像素的总光子预算的立方根成比例,解析规则设定了如何在通量和视图之间分配该预算。我们在代表性临床前微CT扫描仪上说明了该框架,通过对通量和投影计数的参数扫描展示了每个采集参数如何重塑分辨率图。一个随附的开源网络计算器为任意扫描仪几何形状实现了这些极限。

英文摘要

Spatial resolution in preclinical cone-beam micro-CT is bounded by two reconstruction-independent limits, a photon-noise limit from the projection-domain signal-known-exactly, background-known-exactly (SKE/BKE) ideal observer with the Rose criterion, and an angular-sampling limit from the Crowther criterion. The photon-noise bound is a property of the input data and applies to any reconstruction algorithm. The angular-sampling bound applies to classical analytic and iterative reconstructions (FDK, FBP, SIRT) that do not inject signal priors. We derive both limits in closed form for a circular feature in a uniform background, including an off-axis fan-beam extension, and combine them into a spatially varying effective resolution map. The combined limit yields a closed-form scan-design optimum. The maximum worst-case spatial frequency scales as the cube root of the total photon budget per detector pixel (per-view flux times number of views), and an analytic rule sets how to split that budget between flux and views. We illustrate the framework on a representative preclinical micro-CT scanner, with parametric sweeps over flux and projection count that show how each acquisition parameter reshapes the resolution map. An accompanying open-source web calculator implements these bounds for arbitrary scanner geometries.

CommentsAccompanying open-source interactive web calculator: https://ubc-ford-lab.github.io/ideal_observer_SKE_BKE_model/

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