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A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images
Deep learning (DL) has recently been successfully applied to a number of image analysis problems. However, DL approaches tend to be inefficient for segmentation on large image data, such as high-resolution digital pathology slide images. For example, typical breast biopsy images scanned at 40× magni...
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| Veröffentlicht in: | Comput Methods Biomech Biomed Eng Imaging Vis |
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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/PMC5935259/ https://ncbi.nlm.nih.gov/pubmed/29732269 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/21681163.2016.1141063 |
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