Improving reproducibility and performance of radiomics in low‐dose CT using cycle GANs

BACKGROUND: As a means to extract biomarkers from medical imaging, radiomics has attracted increased attention from researchers. However, reproducibility and performance of radiomics in low‐dose CT scans are still poor, mostly due to noise. Deep learning generative models can be used to denoise thes...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Junhua, Wee, Leonard, Dekker, Andre, Bermejo, Inigo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9588275/
https://www.ncbi.nlm.nih.gov/pubmed/35906893
http://dx.doi.org/10.1002/acm2.13739

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9588275/
https://www.ncbi.nlm.nih.gov/pubmed/35906893
http://dx.doi.org/10.1002/acm2.13739

Ejemplares similares