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A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching
We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be...
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| Main Authors: | , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
2013
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3680373/ https://ncbi.nlm.nih.gov/pubmed/23568787 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/cyto.a.22280 |
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