469 citations · 1.4k across the 20 of their papers we have counts for
3 papers · 2 filters
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…
Decoupling Semantic Similarity from Spatial Alignment for Neural Networks
Tassilo Wald, Constantin Ulrich, Gregor Köhler +6
What representation do deep neural networks learn? How similar are images to each other for neural networks? Despite the overwhelming success of deep learning methods key questions…
nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation
Fabian Isensee, Tassilo Wald, Constantin Ulrich +4
The release of nnU-Net marked a paradigm shift in 3D medical image segmentation, demonstrating that a properly configured U-Net architecture could still achieve state-of-the-art re…