Identification of macrotrabecular‐massive hepatocellular carcinoma through multiphasic CT‐based representation learning method
Multiphasic radiomics features of AP and PVP fused by the MCLFF have demonstrated substantial potential in the accurate prediction of MTM HCC. Clinical factors and Radiological features in mpCECT contribute incremental values to the developed MCLFF strategy.
Authors
- Zhenyang Zhang (ORCID: https://orcid.org/0000-0002-2544-2070)
- Xin Zhen (ORCID: https://orcid.org/0000-0002-5037-2801)
- Jincheng Xie
- Ruimeng Yang
- Yandong Zhao (ORCID: https://orcid.org/0000-0001-8661-0229)
- Xinqing Jiang (ORCID: https://orcid.org/0000-0003-3381-429X)
- Fangrong Liang
- Xinhua Wei (ORCID: https://orcid.org/0000-0003-1074-4612)
- Wanli Zhang (ORCID: https://orcid.org/0000-0002-6401-0342)
- Shengsheng Lai
- Tan Lilian
- Chutong He
Institutions
- Second Affiliated Hospital of Guangzhou Medical University (CN)
- Guangzhou First People's Hospital (CN)
- Guangdong Academy of Medical Sciences (CN)
- Guangdong Food and Drug Vocational College (CN)
- Guangdong Provincial People's Hospital (CN)
- First Affiliated Hospital of Jinan University (CN)
- Southern Medical University (CN)
- South China University of Technology (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1002/mp.17401
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- Basic and Applied Basic Research Foundation of Guangdong Province