论文标题
关于分割注释的变化的小笔记
A small note on variation in segmentation annotations
论文作者
论文摘要
我们报告了在2020年丹麦生物成像网络会议上举行的机器学习研讨会上进行的小型众包实验的结果。在研讨会期间，我们要求参与者在三个2D补丁中手动分段线粒体。实验的目的是说明不应将手动注释视为基础真理，而应将其视为具有实质性变化的参考标准。在本说明中，我们显示了如何通过以最差的配对一致性去除注释者来减少分割中观察到的大变化。在以最差的性能去除注释者之后，我们说明其余方差在语义上是有意义的，可以利用以获得细胞边界和细胞内部的分割。
We report on the results of a small crowdsourcing experiment conducted at a workshop on machine learning for segmentation held at the Danish Bio Imaging network meeting 2020. During the workshop we asked participants to manually segment mitochondria in three 2D patches. The aim of the experiment was to illustrate that manual annotations should not be seen as the ground truth, but as a reference standard that is subject to substantial variation. In this note we show how the large variation we observed in the segmentations can be reduced by removing the annotators with worst pair-wise agreement. Having removed the annotators with worst performance, we illustrate that the remaining variance is semantically meaningful and can be exploited to obtain segmentations of cell boundary and cell interior.
