| _version_ | 1866902296063901696 |
|---|---|
| author | Van De Looverbosch, Tim De Beuckeleer, Sarah De Vos, Winnok H. |
| author_facet | Van De Looverbosch, Tim De Beuckeleer, Sarah De Vos, Winnok H. |
| contents | Proximity Adjusted Centroid MAPping (PAC-MAP) is a novel and deep learning-based method for nuclei detection in 3D light microscopy images of (dense) 3D cell systems with a nuclear-specific stain. It works by predicting proximity adjusted centroid probability maps in which nuclei locations are found as local maxima. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17357495 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | DeVosLab/PAC-MAP: v1.0.1 Van De Looverbosch, Tim De Beuckeleer, Sarah De Vos, Winnok H. Proximity Adjusted Centroid MAPping (PAC-MAP) is a novel and deep learning-based method for nuclei detection in 3D light microscopy images of (dense) 3D cell systems with a nuclear-specific stain. It works by predicting proximity adjusted centroid probability maps in which nuclei locations are found as local maxima. |
| title | DeVosLab/PAC-MAP: v1.0.1 |
| url | https://doi.org/10.5281/zenodo.17357495 |