Improving feature extraction from histopathological images through a fine-tuning ImageNet model

BACKGROUND: Due to lack of annotated pathological images, transfer learning has been the predominant approach in the field of digital pathology. Pre-trained neural networks based on ImageNet database are often used to extract “off-the-shelf” features, achieving great success in predicting tissue typ...

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Detalles Bibliográficos
Autores principales: Li, Xingyu, Cen, Min, Xu, Jinfeng, Zhang, Hong, Xu, Xu Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577036/
https://www.ncbi.nlm.nih.gov/pubmed/36268072
http://dx.doi.org/10.1016/j.jpi.2022.100115

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577036/
https://www.ncbi.nlm.nih.gov/pubmed/36268072
http://dx.doi.org/10.1016/j.jpi.2022.100115

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