Glomerular Classification Using Convolutional Neural Networks Based on Defined Annotation Criteria and Concordance Evaluation Among Clinicians

INTRODUCTION: Diagnosing renal pathologies is important for performing treatments. However, classifying every glomerulus is difficult for clinicians; thus, a support system, such as a computer, is required. This paper describes the automatic classification of glomerular images using a convolutional...

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Detalles Bibliográficos
Autores principales: Yamaguchi, Ryohei, Kawazoe, Yoshimasa, Shimamoto, Kiminori, Shinohara, Emiko, Tsukamoto, Tatsuo, Shintani-Domoto, Yukako, Nagasu, Hajime, Uozaki, Hiroshi, Ushiku, Tetsuo, Nangaku, Masaomi, Kashihara, Naoki, Shimizu, Akira, Nagata, Michio, Ohe, Kazuhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Clinical Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938073/
https://www.ncbi.nlm.nih.gov/pubmed/33732986
http://dx.doi.org/10.1016/j.ekir.2020.11.037

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938073/
https://www.ncbi.nlm.nih.gov/pubmed/33732986
http://dx.doi.org/10.1016/j.ekir.2020.11.037

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