Code-Free Development and Deployment of Deep Segmentation Models for Digital Pathology

Application of deep learning on histopathological whole slide images (WSIs) holds promise of improving diagnostic efficiency and reproducibility but is largely dependent on the ability to write computer code or purchase commercial solutions. We present a code-free pipeline utilizing free-to-use, ope...

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Detalles Bibliográficos
Autores principales: Pettersen, Henrik Sahlin, Belevich, Ilya, Røyset, Elin Synnøve, Smistad, Erik, Simpson, Melanie Rae, Jokitalo, Eija, Reinertsen, Ingerid, Bakke, Ingunn, Pedersen, André
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8829033/
https://www.ncbi.nlm.nih.gov/pubmed/35155486
http://dx.doi.org/10.3389/fmed.2021.816281

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8829033/
https://www.ncbi.nlm.nih.gov/pubmed/35155486
http://dx.doi.org/10.3389/fmed.2021.816281

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