A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer

The success of training computer-vision models heavily relies on the support of large-scale, real-world images with annotations. Yet such an annotation-ready dataset is difficult to curate in pathology due to the privacy protection and excessive annotation burden. To aid in computational pathology,...

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Detalles Bibliográficos
Autores principales: Ding, Kexin, Zhou, Mu, Wang, He, Gevaert, Olivier, Metaxas, Dimitris, Zhang, Shaoting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121551/
https://www.ncbi.nlm.nih.gov/pubmed/37085533
http://dx.doi.org/10.1038/s41597-023-02125-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121551/
https://www.ncbi.nlm.nih.gov/pubmed/37085533
http://dx.doi.org/10.1038/s41597-023-02125-y

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