Although several metal artifact reduction (MAR) algorithms for computed tomography (CT) scanning are commercially available, no quantitative, rigorous, and reproducible method exists for assessing their performance. The lack of assessment methods poses a challenge to regulators, consumers, and industry. We explored a phantom‐based framework for assessing an important aspect of MAR performance: how applying MAR in the presence of metal affects model observer performance at a low‐contrast detectability (LCD) task This work is, to our knowledge, the first model observer–based framework for the evaluation of MAR algorithms in the published literature.

中文翻译：

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CT金属伪影减少算法：建立客观性能评估的框架。

尽管有几种用于计算机断层扫描（CT）扫描的金属伪影减少（MAR）算法是可商购的，但尚无用于评估其性能的定量，严格和可重现的方法。缺乏评估方法对监管者，消费者和行业构成了挑战。我们探索了一种基于幻影的框架来评估MAR性能的重要方面：在低对比度可检测性（LCD）任务下，在金属存在下应用MAR如何影响模型观察者的性能据我们所知，这是第一位模型观察者文献中基于MAR的MAR算法评估框架。