Impact of deep learning image reconstruction algorithms on CT radiomic features in patients with liver tumors

OBJECTIVE: To evaluate the impact of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) on abdominal CT radiomic features acquired in portal venous phase in liver tumor patients. METHODS: Sixty patients with liver tumors who underwent contrast-en...

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Detalles Bibliográficos
Autores principales: Xue, Gongbo, Liu, Hongyan, Cai, Xiaoyi, Zhang, Zhen, Zhang, Shuai, Liu, Ling, Hu, Bin, Wang, Guohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113560/
https://www.ncbi.nlm.nih.gov/pubmed/37091167
http://dx.doi.org/10.3389/fonc.2023.1167745

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113560/
https://www.ncbi.nlm.nih.gov/pubmed/37091167
http://dx.doi.org/10.3389/fonc.2023.1167745

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