Accurate classification of major brain cell types using in vivo imaging and neural network processing
This dataset accompanies the article of the same title in the journal Plos Biology. It includes a) Ground truth datasets for the training of the StarDist neuronal network for nucleus segmentation (StardistTraining.tar.gz) b) The trained Stardist nucleus segmentation model (StardistModel.tar.gz c) ra...
Gespeichert in:
| 1. Verfasser: | |
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| Dokumenttyp: | Datenbank Forschungsdaten |
| Sprache: | Englisch |
| Veröffentlicht: |
Heidelberg
Universität
2023-09-18
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| DOI: | 10.11588/data/L3PITA |
| Schlagworte: | |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.11588/data/L3PITA Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/L3PITA 
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| Verfasserangaben: | Johannes Knabbe |
MARC
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| 520 | |a This dataset accompanies the article of the same title in the journal Plos Biology. It includes a) Ground truth datasets for the training of the StarDist neuronal network for nucleus segmentation (StardistTraining.tar.gz) b) The trained Stardist nucleus segmentation model (StardistModel.tar.gz c) raw and segmented data for the training of the cell type classification (CelltypeClassification.tar.gz, CelltypeClassificationExcInhNeurons.tar.gz) d) the raw and segmented data for the results of the paper (RawdataResults.tar.gz) e) Ground truth data for the training of all classifiers (ClassificationTrainingDataSet.tab) | ||
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