Differential cell counts using center-point networks achieves human-level accuracy and efficiency over segmentation
Abstract Differential cell counts is a challenging task when applying computer vision algorithms to pathology. Existing approaches to train cell recognition require high availability of multi-class segmentation and/or bounding box annotations and suffer in performance when objects are tightly cluste...
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Auteurs principaux: | , , , , |
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Format: | article |
Langue: | EN |
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Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/bc5ecf7f2ac74511b28084801ee0ef06 |
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