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Application of Tolerance Limits to the Characterization of Image Registration Performance

机译:公差极限在图像配准性能表征中的应用

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摘要

Deformable image registration is used increasingly in image-guided interventions and other applications. However, validation and characterization of registration performance remain areas that require further study. We propose an analysis methodology for deriving tolerance limits on the initial conditions for deformable registration that reliably lead to a successful registration. This approach results in a concise summary of the probability of registration failure, while accounting for the variability in the test data. The (β, γ) tolerance limit can be interpreted as a value of the input parameter that leads to successful registration outcome in at least 100β% of cases with the 100γ% confidence. The utility of the methodology is illustrated by summarizing the performance of a deformable registration algorithm evaluated in three different experimental setups of increasing complexity. Our examples are based on clinical data collected during MRI-guided prostate biopsy registered using publicly available deformable registration tool. The results indicate that the proposed methodology can be used to generate concise graphical summaries of the experiments, as well as a probabilistic estimate of the registration outcome for a future sample. Its use may facilitate improved objective assessment, comparison and retrospective stress-testing of deformable.
机译:可变形图像配准在图像引导干预和其他应用中越来越多地使用。但是,注册性能的验证和表征仍然是需要进一步研究的领域。我们提出一种分析方法,以得出可变形套准的初始条件的公差极限,该公差可靠地导致成功套准。这种方法可得出注册失败概率的简要摘要,同时考虑了测试数据的可变性。 (β,γ)公差极限可以解释为输入参数的值,该输入参数在至少100β%的情况下以100γ%的置信度导致成功的配准结果。通过汇总在增加复杂性的三个不同实验设置中评估的可变形配准算法的性能来说明该方法的实用性。我们的示例基于使用可公开获得的可变形注册工具在MRI指导的前列腺活检过程中收集的临床数据。结果表明,所提出的方法可用于生成实验的简明图形摘要,以及将来样本的配准结果的概率估计。它的使用可能有助于改进可变形物体的客观评估,比较和回顾性压力测试。

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