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5 papers · 1 filter
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…
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…
How Shift Equivariance Impacts Metric Learning for Instance Segmentation
Josef Lorenz Rumberger, Xiaoyan Yu, Peter Hirsch +6
Metric learning has received conflicting assessments concerning its suitability for solving instance segmentation tasks. It has been dismissed as theoretically flawed due to the sh…
Probabilistic Deep Learning for Instance Segmentation
Josef Lorenz Rumberger, Lisa Mais, Dagmar Kainmueller
Probabilistic convolutional neural networks, which predict distributions of predictions instead of point estimates, led to recent advances in many areas of computer vision, from im…
Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting
Jackie Ma, Maximilian März, Stephanie Funk +4
High-resolution three-dimensional (3D) cardiovascular magnetic resonance (CMR) is a valuable medical imaging technique, but its widespread application in clinical practice is hampe…