Deterministic small‐scale undulations of image‐based risk predictions from the deep learning of lung tumors in motion

INTRODUCTION: Deep learning (DL) models that use medical images to predict clinical outcomes are poised for clinical translation. For tumors that reside in organs that move, however, the impact of motion (i.e., degenerated object appearance or blur) on DL model accuracy remains unclear. We examine t...

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Detalles Bibliográficos
Autores principales: Teo, P. Troy, Bajaj, Amishi, Randall, James, Lou, Bin, Shah, Jainil, Gopalakrishnan, Mahesh, Kamen, Ali, Abazeed, Mohamed E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
BIOLOGICAL PHYSICS AND RESPONSE PREDICTION
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115400/
https://www.ncbi.nlm.nih.gov/pubmed/35962958
http://dx.doi.org/10.1002/mp.15869

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115400/
https://www.ncbi.nlm.nih.gov/pubmed/35962958
http://dx.doi.org/10.1002/mp.15869

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