Segmentation metric misinterpretations in bioimage analysis
Dominik Hirling, Ervin Tasnádi, Juan Carlos Caicedo, Maria Caroprese, Rickard Sjögren, Marc Aubreville, Krisztián Koós, Péter Horváth
Abstract
Quantitative evaluation of image segmentation algorithms is crucial in the field of bioimage analysis. The most common assessment scores, however, are often misinterpreted and multiple definitions coexist with the same name. Here we present the ambiguities of evaluation metrics for segmentation algorithms and show how these misinterpretations can alter leaderboards of influential competitions. We also propose guidelines for how the currently existing problems could be tackled.
Topics & Concepts
SegmentationComputer scienceMetric (unit)Field (mathematics)Artificial intelligenceImage segmentationImage (mathematics)Machine learningPattern recognition (psychology)MathematicsOperations managementEconomicsPure mathematicsCell Image Analysis TechniquesImage Processing Techniques and ApplicationsSingle-cell and spatial transcriptomics