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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...
Autores principales: | Kitahara, Hitoshi, Nagatani, Yukihiro, Otani, Hideji, Nakayama, Ryohei, Kida, Yukako, Sonoda, Akinaga, Watanabe, Yoshiyuki |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
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Materias: | |
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 |
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