A small note on variation in segmentation annotations

Research output: Contribution to journalJournal articleResearch

  • Silas Nyboe Ørting
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.
Original languageEnglish
Number of pages6
Publication statusPublished - 3 Dec 2020

    Research areas

  • cs.CV, cs.HC

ID: 253071786