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Automatic segmentation variability estimation with segmentation priors

机译:分割前沿自动分割变化估计

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摘要

Purpose: Segmentations produced manually by experts or by algorithms are subject to variability, as they depend on many factors, e.g., the structure of interest, the resolution, contrast and quality of the images, and the expert experience or the algorithmic method. To properly assess the quality of these segmentations, it is thus essential to quantify their variability. However, obtaining reference variability ground truth requires several observers to manually delineate structures, which is time-consuming and impractical.
机译:目的:由专家或算法手动生产的分割受到可变性的影响,因为它们依赖于许多因素,例如感兴趣的结构,图像的分辨率,对比度和质量以及专家体验或算法方法。 为了适当地评估这些分段的质量,因此必须量化其变异性必不可少。 然而,获得参考可变性地面真理需要几个观察者手动描绘结构,这是耗时和不切实际的。

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