The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model

We evaluated a multiclass classification model to predict estimated glomerular filtration rate (eGFR) groups in chronic kidney disease (CKD) patients using magnetic resonance imaging (MRI) texture analysis (TA). We identified 166 CKD patients who underwent MRI comprising Dixon-based T1-weighted in-p...

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Detalles Bibliográficos
Autores principales: Hara, Yuki, Nagawa, Keita, Yamamoto, Yuya, Inoue, Kaiji, Funakoshi, Kazuto, Inoue, Tsutomu, Okada, Hirokazu, Ishikawa, Masahiro, Kobayashi, Naoki, Kozawa, Eito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427930/
https://www.ncbi.nlm.nih.gov/pubmed/36042326
http://dx.doi.org/10.1038/s41598-022-19009-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427930/
https://www.ncbi.nlm.nih.gov/pubmed/36042326
http://dx.doi.org/10.1038/s41598-022-19009-7

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