Labelling instructions matter in biomedical image analysis

Tim Rädsch, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Nicholas Schreck, A. Emre Kavur, Bünyamin Pekdemir, Tobias Roß, Annette Kopp-Schneider, Lena Maier-Hein

Abstract: High-quality annotation of datasets is critical for machine-learning-based biomedical image analysis. However, a detailed examination of recent image competitions reveals a gap between annotators’ needs and quality of labelling instructions. It is also found that annotator performance can be substantially improved by providing exemplary images.