469 citations · 1.1k across the 5 of their papers we have counts for
5 papers
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Confidence estimation of classification based on the distribution of the neural network output layer
Abdel Aziz Taha, Leonhard Hennig, Petr Knoth
One of the most common problems preventing the application of prediction models in the real world is lack of generalization: The accuracy of models, measured in the benchmark does…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
On The Usage Of Average Hausdorff Distance For Segmentation Performance Assessment: Hidden Bias When Used For Ranking
Orhun Utku Aydin, Abdel Aziz Taha, Adam Hilbert +5
Average Hausdorff Distance (AVD) is a widely used performance measure to calculate the distance between two point sets. In medical image segmentation, AVD is used to compare ground…
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke +35
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of c…