Evaluation of a Generative Adversarial Network to Improve Image Quality and Reduce Radiation-Dose during Digital Breast Tomosynthesis

In this study, we evaluated the improvement of image quality in digital breast tomosynthesis under low-radiation dose conditions of pre-reconstruction processing using conditional generative adversarial networks [cGAN (pix2pix)]. Pix2pix pre-reconstruction processing with filtered back projection (F...

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Detalles Bibliográficos
Autores principales: Gomi, Tsutomu, Kijima, Yukie, Kobayashi, Takayuki, Koibuchi, Yukio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871529/
https://www.ncbi.nlm.nih.gov/pubmed/35204582
http://dx.doi.org/10.3390/diagnostics12020495

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871529/
https://www.ncbi.nlm.nih.gov/pubmed/35204582
http://dx.doi.org/10.3390/diagnostics12020495

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