Deep Segmentation Feature-Based Radiomics Improves Recurrence Prediction of Hepatocellular Carcinoma

Objective and Impact Statement. This study developed and validated a deep semantic segmentation feature-based radiomics (DSFR) model based on preoperative contrast-enhanced computed tomography (CECT) combined with clinical information to predict early recurrence (ER) of single hepatocellular carcino...

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Detalles Bibliográficos
Autores principales: Wang, Jifei, Wu, Dasheng, Sun, Meili, Peng, Zhenpeng, Lin, Yingyu, Lin, Hongxin, Chen, Jiazhao, Long, Tingyu, Li, Zi-Ping, Xie, Chuanmiao, Huang, Bingsheng, Feng, Shi-Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521680/
https://www.ncbi.nlm.nih.gov/pubmed/37850181
http://dx.doi.org/10.34133/2022/9793716

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521680/
https://www.ncbi.nlm.nih.gov/pubmed/37850181
http://dx.doi.org/10.34133/2022/9793716

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