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A Supervised Learning Framework for Pancreatic Islet Segmentation With Multi-Scale Color-Texture Features and Rolling Guidance Filters
Islet cell quantification and function is important for developing novel therapeutic interventions for diabetes. Existing methods of pancreatic islet segmentation in histopathological images depend strongly on cell/nuclei detection, and thus are limited due to a wide variance in the appearance of pa...
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| Veröffentlicht in: | Cytometry A |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2016
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5515086/ https://ncbi.nlm.nih.gov/pubmed/27560544 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/cyto.a.22929 |
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