Learning from scanners: Bias reduction and feature correction in radiomics

PURPOSE: Radiomics are quantitative features extracted from medical images. Many radiomic features depend not only on tumor properties, but also on non-tumor related factors such as scanner signal-to-noise ratio (SNR), reconstruction kernel and other image acquisition settings. This causes undesirab...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhovannik, Ivan, Bussink, Johan, Traverso, Alberto, Shi, Zhenwei, Kalendralis, Petros, Wee, Leonard, Dekker, Andre, Fijten, Rianne, Monshouwer, René
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690665/
https://www.ncbi.nlm.nih.gov/pubmed/31417963
http://dx.doi.org/10.1016/j.ctro.2019.07.003

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690665/
https://www.ncbi.nlm.nih.gov/pubmed/31417963
http://dx.doi.org/10.1016/j.ctro.2019.07.003

Ejemplares similares