A deep-learning toolkit for visualization and interpretation of segmented medical images

Generalizability of deep-learning (DL) model performance is not well understood and uses anecdotal assumptions for increasing training data to improve segmentation of medical images. We report statistical methods for visual interpretation of DL models trained using ImageNet initialization with natur...

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Detalles Bibliográficos
Autores principales: Ghosal, Sambuddha, Shah, Pratik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017181/
https://www.ncbi.nlm.nih.gov/pubmed/35474999
http://dx.doi.org/10.1016/j.crmeth.2021.100107

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017181/
https://www.ncbi.nlm.nih.gov/pubmed/35474999
http://dx.doi.org/10.1016/j.crmeth.2021.100107

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