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Automatic border detection in intravascular iltrasound images for quantitative measurements of the vessel, lumen and stent parameters

机译:血管内超声图像中的自动边界检测,用于血管,内腔和支架参数的定量测量

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The automated segmentation of lumen, vessel and stent boundaries in intravascular ultrasound (IMS) images will reduce the required analysis time and the subjectivity of the commonly used manual tracing procedure while the three-dimensional reconstruction permits an advanced assessment of the morphology. We describe a knowledge and model guided system for the (semi-) automatic contour detection of these borders. The different steps of a complete analysis of an IVUS pullback sequence are carried out such, that the different components assist each other. The stent detection assists the vessel detection and both detections assist the lumen detection. The results of the detection show a very good correlation with manually drawn contours. Due to the flexible use of more than two longitudinal cut planes and the advanced knowledge-guided contour detection approach, the new IVUS analysis system has proven to be suitable for clinical research-studies.
机译:内腔,血管和支架边界的自动分割在血管内超声(IMS)图像中将减少所需的分析时间和常用的手动跟踪程序的主体性,而三维重建允许对形态进行高级评估。我们描述了(半)自动轮廓检测的知识和模型引导系统。执行IVUS回拉序列的完全分析的不同步骤,使得不同的组件互相辅助。支架检测有助于血管检测,并且两个检测都辅助腔检测。检测结果显示与手动绘制的轮廓非常好的相关性。由于使用两个以上的纵向切割平面和先进的知识导向轮廓检测方法,新的IVUS分析系统已被证明适用于临床研究 - 研究。

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