OrganoidTracker: Efficient cell tracking using machine learning and manual error correction
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Title
OrganoidTracker: Efficient cell tracking using machine learning and manual error correction
Authors
Keywords
Neural networks, Organoids, Cell cycle and cell division, Memory recall, Computer software, Gastrointestinal tract, Fluorescence imaging, Cell differentiation
Journal
PLoS One
Volume 15, Issue 10, Pages e0240802
Publisher
Public Library of Science (PLoS)
Online
2020-10-23
DOI
10.1371/journal.pone.0240802
References
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- Tales from the crypt: new insights into intestinal stem cells
- (2018) Helmuth Gehart et al. Nature Reviews Gastroenterology & Hepatology
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- (2018) Elizabeth Pennisi SCIENCE
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- (2017) Thomas E. Wallach et al. JOURNAL OF PEDIATRIC GASTROENTEROLOGY AND NUTRITION
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- scikit-image: image processing in Python
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