TopoMortar：一个用于评估关注拓扑精度的图像分割方法的数据集
TopoMortar: A dataset to evaluate image segmentation methods focused on topology accuracy
AI总结：
本文提出首个专门评估拓扑精度分割方法的砖墙数据集TopoMortar，通过隔离数据集挑战比较八种损失函数，发现clDice拓扑精度最高，并证明数据增强与自蒸馏可提升拓扑分割性能。
摘要：
我们提出了TopoMortar，一个砖墙数据集，它是第一个专门为评估关注拓扑的图像分割方法（如拓扑损失函数）而设计的数据集。由于方法对数据集挑战（如小训练集、噪声标签和分布外测试集图像）的敏感性是已知的，因此创建TopoMortar是为了以两种方式研究各种方法在提高拓扑精度方面的有效性。第一，通过消除数据集挑战，正如我们所展示的，这些挑战会影响拓扑损失函数的有效性。第二，通过允许在同一数据集中表示不同的数据集挑战，将方法的性能与数据集挑战隔离开来。TopoMortar包括三种类型的标签（准确标签、伪标签和噪声标签）、两个固定的训练集（大和小），以及分布内和分布外的测试集图像。我们在TopoMortar上比较了八种损失函数，发现clDice实现了拓扑上最准确的分割，并且其他损失函数的相对优势取决于实验设置。此外，我们表明数据增强和自蒸馏可以将Cross entropy Dice loss提升到超越大多数拓扑损失函数的水平，并且这些简单的方法也可以增强拓扑损失函数。TopoMortar和我们的代码可以在https://jmlipman.github.io/TopoMortar找到。
英文摘要：
We present TopoMortar, a brick wall dataset that is the first dataset specifically designed to evaluate topology-focused image segmentation methods, such as topology loss functions. Motivated by the known sensitivity of methods to dataset challenges, such as small training sets, noisy labels, and out-of-distribution test-set images, TopoMortar is created to enable in two ways investigating methods' effectiveness at improving topology accuracy. First, by eliminating dataset challenges that, as we show, impact the effectiveness of topology loss functions. Second, by allowing to represent different dataset challenges in the same dataset, isolating methods' performance from dataset challenges. TopoMortar includes three types of labels (accurate, pseudo-labels, and noisy labels), two fixed training sets (large and small), and in-distribution and out-of-distribution test-set images. We compared eight loss functions on TopoMortar, and we found that clDice achieved the most topologically accurate segmentations, and that the relative advantageousness of the other loss functions depends on the experimental setting. Additionally, we show that data augmentation and self-distillation can elevate Cross entropy Dice loss to surpass most topology loss functions, and that those simple methods can enhance topology loss functions as well. TopoMortar and our code can be found at https://jmlipman.github.io/TopoMortar
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
