Multi-Modality Microscopy Image Style Augmentation for Nuclei Segmentation

Annotating microscopy images for nuclei segmentation by medical experts is laborious and time-consuming. To leverage the few existing annotations, also across multiple modalities, we propose a novel microscopy-style augmentation technique based on a generative adversarial network (GAN). Unlike other...

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Detalles Bibliográficos
Autores principales: Liu, Ye, Wagner, Sophia J., Peng, Tingying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948875/
https://www.ncbi.nlm.nih.gov/pubmed/35324626
http://dx.doi.org/10.3390/jimaging8030071

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948875/
https://www.ncbi.nlm.nih.gov/pubmed/35324626
http://dx.doi.org/10.3390/jimaging8030071

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