nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation is one of 9,000 studies in the ScholarPulse dataset. Key details — Authors: Fabian Isensee, Paul F. Jaeger, Simon A. A. Kohl, Jens Petersen, Klaus H. Maier-Hein; Journal / source: Nature Methods; Year: 2020.
| Authors | Fabian Isensee, Paul F. Jaeger, Simon A. A. Kohl, Jens Petersen, Klaus H. Maier-Hein |
|---|---|
| Journal / source | Nature Methods |
| Year | 2020 |
| Field | Advanced Neural Network Applications |
| Times cited | 8459 |
| Type | article |
| DOI / link | https://doi.org/10.1038/s41592-020-01008-z |