Model card
nnU-Net v2.
German Cancer Research Center (DKFZ)open-sourcevaries (~31M default) paramsU-Net (self-configuring)
Self-configuring U-Net framework. De facto baseline for medical image segmentation. v2 adds improved preprocessing and more architectures.
§ 01 · Benchmarks
Every benchmark nnU-Net v2 has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | ACDC | Medical · Medical Image Segmentation | mean-dsc | 91.6% | #2 | 2023-03-17 | source ↗ |
| 02 | BraTS 2023 | Medical · Medical Image Segmentation | mean-dice-wt-tc-et | 0.9% | #3 | 2024-06-11 | source ↗ |
| 03 | BTCV | Medical · Medical Image Segmentation | mean-dsc | 81.8% | #3 | 2023-04-13 | source ↗ |
| 04 | Synapse Multi-Organ CT | Medical · Medical Image Segmentation | mean-dsc | 82.5% | #7 | 2023-03-17 | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Papers
3 papers with results for nnU-Net v2.
- 2024-06-11· Medical· 1 result
nnU-Net for BraTS 2023: Adaptation of nnU-Net for BraTS 2023
- 2023-04-13· Medical· 1 result
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training
- 2023-03-17· Medical· 2 results
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
§ 04 · Related models
Other German Cancer Research Center (DKFZ) models scored on Codesota.
§ 05 · Sources & freshness
Where these numbers come from.
arxiv
4
results
4 of 4 rows marked verified. · first result 2023-03-17, latest 2024-06-11.