Fully automated AI-based splenic segmentation for predicting survival and estimating the risk of hepatic decompensation in TACE patients with HCC

OBJECTIVES: Splenic volume (SV) was proposed as a relevant prognostic factor for patients with hepatocellular carcinoma (HCC). We trained a deep-learning algorithm to fully automatically assess SV based on computed tomography (CT) scans. Then, we investigated SV as a prognostic factor for patients w...

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Detalles Bibliográficos
Autores principales: Müller, Lukas, Kloeckner, Roman, Mähringer-Kunz, Aline, Stoehr, Fabian, Düber, Christoph, Arnhold, Gordon, Gairing, Simon Johannes, Foerster, Friedrich, Weinmann, Arndt, Galle, Peter Robert, Mittler, Jens, Pinto dos Santos, Daniel, Hahn, Felix
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Gastrointestinal
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381627/
https://www.ncbi.nlm.nih.gov/pubmed/35394184
http://dx.doi.org/10.1007/s00330-022-08737-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381627/
https://www.ncbi.nlm.nih.gov/pubmed/35394184
http://dx.doi.org/10.1007/s00330-022-08737-z

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