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Evaluating deformation patterns of the thoracic aorta in gated CTA sequences

机译:评价门控CTA序列中胸主动脉的变形模式

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Cardiovascular interventions in the region of the aortic isthmus such as stent-grafting and vessel transposition introduce substantial changes in the deformation properties of the affected vessels. The changes play a fundamental role in the long-term prognosis for any such treatment, but are only poorly understood to date. We explore a fully automated method to quantify the deformation patterns of the thoracic aorta in gated computed tomography sequences. The aorta is segmented by a level set approach that accurately identifies the vessel lumen in each frame of the sequence. Consequently, landmarks on the vessel wall in each frame are registered using a probabilistic method. This allows for the measurement of global and local deformation properties. We evaluate our method on synthetic datasets and report first results of its application on real world data.
机译:在主动脉峡部区域的心血管干预(例如支架移植和血管移位)会在受影响的血管的变形特性方面产生重大变化。这些变化在任何此类治疗的长期预后中都起着根本性的作用,但迄今为止却鲜为人知。我们探索一种完全自动化的方法来量化门控计算机断层扫描序列中胸主动脉的变形模式。通过水平集方法对主动脉进行分割,该方法可准确识别序列每一帧中的血管腔。因此,使用概率方法在每个帧中记录血管壁上的界标。这允许测量整体和局部变形特性。我们在合成数据集上评估我们的方法,并报告其在现实世界数据上的应用结果。

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