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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: Chen, Cheng, Wang, Wei, Ozolek, John A., Rohde, Gustavo K.
格式: Artigo
語言:Inglês
出版: 2013
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在線閱讀: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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