Cargando…
Improving detection performance of hepatocellular carcinoma and interobserver agreement for liver imaging reporting and data system on CT using deep learning reconstruction
PURPOSE: This study aimed to compare the hepatocellular carcinoma (HCC) detection performance, interobserver agreement for Liver Imaging Reporting and Data System (LI-RADS) categories, and image quality between deep learning reconstruction (DLR) and conventional hybrid iterative reconstruction (Hybr...
Autores principales: | Okimoto, Naomasa, Yasaka, Koichiro, Kaiume, Masafumi, Kanemaru, Noriko, Suzuki, Yuichi, Abe, Osamu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115733/ https://www.ncbi.nlm.nih.gov/pubmed/36757454 http://dx.doi.org/10.1007/s00261-023-03834-z |
Ejemplares similares
-
Dynamic contrast-enhanced CT and clinical features of sarcomatoid hepatocellular carcinoma
por: He, Guangming, et al.
Publicado: (2023) -
Effects of deep learning on radiologists’ and radiology residents’ performance in identifying esophageal cancer on CT
por: Yasaka, Koichiro, et al.
Publicado: (2023) -
Exploring the efficacy of (18)F-FDG PET/CT in hepatocellular carcinoma diagnosis: role of Ki-67 index and tumor differentiation
por: Yin, Yuping, et al.
Publicado: (2023) -
Rib fracture detection in computed tomography images using deep convolutional neural networks
por: Kaiume, Masafumi, et al.
Publicado: (2021) -
CT angiography of abdomen and pelvis in critically ill COVID-19 patients: imaging findings and correlation with the CT chest score
por: Vadvala, Harshna V., et al.
Publicado: (2021)