Deep learning-based cardiothoracic ratio measurement on chest radiograph: accuracy improvement without self-annotation

BACKGROUND: A reproducible and accurate automated approach to measuring cardiothoracic ratio on chest radiographs is warranted. This study aimed to develop a deep learning-based model for estimating the cardiothoracic ratio on chest radiographs without requiring self-annotation and to compare its re...

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Detalles Bibliográficos
Autores principales: Yoshida, Kotaro, Takamatsu, Atsushi, Matsubara, Takashi, Kitagawa, Taichi, Toshima, Fomihito, Tanaka, Rie, Gabata, Toshifumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585545/
https://www.ncbi.nlm.nih.gov/pubmed/37869343
http://dx.doi.org/10.21037/qims-23-187

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585545/
https://www.ncbi.nlm.nih.gov/pubmed/37869343
http://dx.doi.org/10.21037/qims-23-187

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