Efficacy evaluation of 2D, 3D U-Net semantic segmentation and atlas-based segmentation of normal lungs excluding the trachea and main bronchi

This study aimed to examine the efficacy of semantic segmentation implemented by deep learning and to confirm whether this method is more effective than a commercially dominant auto-segmentation tool with regards to delineating normal lung excluding the trachea and main bronchi. A total of 232 non-s...

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Detalles Bibliográficos
Autores principales: Nemoto, Takafumi, Futakami, Natsumi, Yagi, Masamichi, Kumabe, Atsuhiro, Takeda, Atsuya, Kunieda, Etsuo, Shigematsu, Naoyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Regular Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246058/
https://www.ncbi.nlm.nih.gov/pubmed/32043528
http://dx.doi.org/10.1093/jrr/rrz086

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246058/
https://www.ncbi.nlm.nih.gov/pubmed/32043528
http://dx.doi.org/10.1093/jrr/rrz086

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