A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset

PURPOSE: To improve the image quality of inflated fixed cadaveric human lungs by utilizing ultra-high-resolution computed tomography (U-HRCT) as a training dataset for super-resolution processing using deep learning (SR-DL). MATERIALS AND METHODS: Image data of nine cadaveric human lungs were acquir...

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Detalles Bibliográficos
Autores principales: Kitahara, Hitoshi, Nagatani, Yukihiro, Otani, Hideji, Nakayama, Ryohei, Kida, Yukako, Sonoda, Akinaga, Watanabe, Yoshiyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315896/
https://www.ncbi.nlm.nih.gov/pubmed/34318444
http://dx.doi.org/10.1007/s11604-021-01184-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315896/
https://www.ncbi.nlm.nih.gov/pubmed/34318444
http://dx.doi.org/10.1007/s11604-021-01184-8

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