Cross-institutional evaluation of deep learning and radiomics models in predicting microvascular invasion in hepatocellular carcinoma: validity, robustness, and ultrasound modality efficacy comparison

Cross-institutional evaluation of deep learning and radiomics models in predicting microvascular invasion in hepatocellular carcinoma: validity, robustness, and ultrasound modality efficacy comparison

Abstract Purpose To conduct a head-to-head comparison between deep learning (DL) and radiomics models across institutions for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and to investigate the model robustness and generalizability through rigorous internal and external...

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Bibliographic Details
Main Authors: Weibin Zhang, Qihui Guo, Yuli Zhu, Meng Wang, Tong Zhang, Guangwen Cheng, Qi Zhang, Hong Ding
Format: Article
Language:English
Published: BMC 2024-10-01
Series:Cancer Imaging
Subjects:
Deep learning
Radiomics
Contrast-enhanced ultrasound
Microvascular invasion
Head-to-head comparison
Online Access:https://doi.org/10.1186/s40644-024-00790-9
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