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Automatic Alignment of Renal DCE-MRI Image Series for Improvement of Quantitative Tracer Kinetic Studies

机译:肾DCE-MRI图像系列的自动对准,提高定量示踪动力学研究

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Tracer kinetic modeling with dynamic contrast enhanced MRI (DCE-MRI) and the quantification of the kinetic parameters are active fields of research which have the potential to improve the measurement of renal function. However, the strong coronal motion of the kidney in the time series inhibits an accurate assessment of the kinetic parameters. Automatic motion correction is challenging due to the large movement of the kidney and the strong intensity changes caused by the injected bolus. In this work, we improve the quantification results by a template matching motion correction method using a gradient-based similarity measure. Thus, a tedious manual motion correction is replaced by an automatic procedure. The only remaining user interaction is reduced to a selection of a reference slice and a coarse manual segmentation of the kidney in this slice. These steps do not present an overhead to the interaction needed for the assessment of the kinetic parameters. In order to achieve reliable and fast results, we constrain the degrees of freedom for the correction method as far as possible. Furthermore, we compare our method to deformable registration using the same similarity measure. In all our tests, the presented template matching correction was superior to the deformable approach in terms of reliability, leading to more accurate parameter quantification. The evaluation on 10 patient data series with 180-230 images each demonstrate that the quantitative analysis by a two-compartment model can be improved by our method.
机译:具有动态对比增强MRI(DCE-MRI)的示踪剂动力学建模和动力学参数的量化是有源研究领域,具有改善肾功能测量的可能性。然而,时间序列中肾脏的强冠状动作抑制了对动力学参数的准确评估。由于肾脏的较大运动和被注入的推注引起的强烈的强度变化,自动运动校正是挑战。在这项工作中,我们通过使用基于梯度的相似度量来改善模板匹配运动校正方法的量化结果。因此,通过自动过程替换繁琐的手动运动校正。唯一剩余的用户交互被减少到在该切片中的参考切片的选择和肾脏的粗手动分段。这些步骤不会向评估动力学参数所需的相互作用呈现开销。为了获得可靠和快速的结果,我们尽可能地限制了校正方法的自由度。此外,我们将我们的方法与使用相同的相似性度量进行可变形的注册。在所有测试中,所呈现的模板匹配校正在可靠性方面优于可变形的方法,导致更准确的参数量化。 10患者数据序列的评估,其中180-230图像各自证明了通过我们的方法可以改善双隔室模型的定量分析。

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