Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases
Background: Deep learning (DL) is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP). The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events), segmentation (e.g., nuclei), and tissue classi...
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| Hoofdauteurs: | , |
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| Formaat: | Boek |
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Elsevier,
2016-01-01T00:00:00Z.
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| Plaatsingsnummer: |
A1234.567 |
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| Kopie 1 | Beschikbaar |