Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis

OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading. METHODS: Totally 466 patients undergoing partial hepatectomy were enrolled, including 401 with chronic hepat...

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Detalles Bibliográficos
Autores principales: Xue, Li-Yun, Jiang, Zhuo-Yun, Fu, Tian-Tian, Wang, Qing-Min, Zhu, Yu-Li, Dai, Meng, Wang, Wen-Ping, Yu, Jin-Hua, Ding, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160214/
https://www.ncbi.nlm.nih.gov/pubmed/31965257
http://dx.doi.org/10.1007/s00330-019-06595-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160214/
https://www.ncbi.nlm.nih.gov/pubmed/31965257
http://dx.doi.org/10.1007/s00330-019-06595-w

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