Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI

Autor:	Keita Nagawa, Yuki Hara, Kaiji Inoue, Yosuke Yamagishi, Masahiro Koyama, Hirokazu Shimizu, Koichiro Matsuura, Iichiro Osawa, Tsutomu Inoue, Hirokazu Okada, Naoki Kobayashi, Eito Kozawa
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	Three-dimensional convolutional neural network Deep learning Chronic kidney disease Magnetic resonance imaging Dixon-based T1-weighted image Medicine Science
Zdroj:	Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Druh dokumentu:	article
ISSN:	2045-2322
DOI:	10.1038/s41598-024-66814-3
Popis:	Abstract A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR]
Databáze:	Directory of Open Access Journals
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