Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.

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Title: Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.
Authors: Gu M; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China., Zou W; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China., Chen H; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China., He R; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China., Zhao X; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China., Jia N; Department of Radiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China., Liu W; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China., Wang P; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China. peijunwangtjyy@163.com.
Source: Cancer imaging : the official publication of the International Cancer Imaging Society [Cancer Imaging] 2025 Jul 07; Vol. 25 (1), pp. 87. Date of Electronic Publication: 2025 Jul 07.
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101172931 Publication Model: Electronic Cited Medium: Internet ISSN: 1470-7330 (Electronic) Linking ISSN: 14707330 NLM ISO Abbreviation: Cancer Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.
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  Data: <searchLink fieldCode="AU" term="%22Gu+M%22">Gu M</searchLink>; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Zou+W%22">Zou W</searchLink>; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Chen+H%22">Chen H</searchLink>; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22He+R%22">He R</searchLink>; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Zhao+X%22">Zhao X</searchLink>; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Jia+N%22">Jia N</searchLink>; Department of Radiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Liu+W%22">Liu W</searchLink>; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Wang+P%22">Wang P</searchLink>; Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China. peijunwangtjyy@163.com.
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  Data: <searchLink fieldCode="JN" term="%22101172931%22">Cancer imaging : the official publication of the International Cancer Imaging Society</searchLink> [Cancer Imaging] 2025 Jul 07; Vol. 25 (1), pp. 87. <i>Date of Electronic Publication: </i>2025 Jul 07.
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        Value: 10.1186/s40644-025-00895-9
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              Text: 2025 Jul 07
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