Data from H&E human bone marrow whole slide scanner images used in the paper: "MarrowQuant 2.0: a digital pathology workflow assisting bone marrow evaluation in clinical and experimental hematology" (https://doi.org/10.21203/rs.3.rs-1860140/v1) 292 image patches Ground truth were manually annotated using QuPath and split into 263 images for training and 29 for validation. Training in StarDist was done on a Windows 10 PC with an RTX 2080 GPU. The requirements file for installing a Python 3.7 environment to run the attached notebooks is provided (stardist-val.txt). The StarDist model configuration can be found in the Jupyter Notebook : Adipocyte Training.ipynb Model validation and metrics can be performed by running the notebook after finishing the Adipocyte Training notebook. Quality Control.ipynb

{"references": ["Rita Sarkis, Olivier Burri, Claire Royer-Chardon et al. MarrowQuant 2.0: a digital pathology workflow assisting bone marrow evaluation in clinical and experimental hematology, 22 July 2022, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-1860140/v1]"]}