Predictive performance of radiomic models based on features extracted from pretrained deep networks

OBJECTIVES: In radiomics, generic texture and morphological features are often used for modeling. Recently, features extracted from pretrained deep networks have been used as an alternative. However, extracting deep features involves several decisions, and it is unclear how these affect the resultin...

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Detalles Bibliográficos
Autor principal: Demircioğlu, Aydin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733744/
https://www.ncbi.nlm.nih.gov/pubmed/36484873
http://dx.doi.org/10.1186/s13244-022-01328-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733744/
https://www.ncbi.nlm.nih.gov/pubmed/36484873
http://dx.doi.org/10.1186/s13244-022-01328-y

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