| Property | Value |
|---|
| Working Groups |  Ertürk |
| Subproject | None |
| Open Access |  Yes |
| Publication Type | Journal Article |
| Peer Reviewed | Yes |
| PMID |  33159057 |
| DOI |  10.1038/s41467-020-19449-7 |
| Publication Year | 2020 |
| Title | Deep learning-enabled multi-organ segmentation in whole-body mouse scans.  |
| Journal | Nature communications |
| ESSN | 2041-1723 |
| URL | https://www.ncbi.nlm.nih.gov/pubmed/?term=33159057%5Buid%5D |
| Pages | 5626 |
| Issue | 1 |
| Volume | 11 |
| Journal Abbreviation | Nat Commun |
| Authors | Schoppe O, Pan C, Coronel J, Mai H, Rong Z, Todorov MI, Müskes A, Navarro F, Li H, Ertürk A, Menze BH |
| First Author | Schoppe O |
| Last Author | Menze BH |
| Scholia |  Wikidata-based representation at Scholia |
External Resources
Q101409844https://www.wikidata.org/wiki/Q101409844
Wikidata ID
