Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals.
Shu-Cheng LiuJesyin LaiJhao-Yu HuangChia-Fong ChoPei Hua LeeMin-Hsuan LuChun-Chieh YehJiaxin YuWei-Ching LinPublished in: Cancer imaging : the official publication of the International Cancer Imaging Society (2021)
This framework provide evidence showing the generalizability and robustness of ResNet-18 in predicting MVI using CT images of AP scanned at multiple different hospitals. Attention heatmaps obtained from model explainability further confirmed that ResNet-18 focused on imaging features on CT overlapping with the conditions used by radiologists to estimate MVI clinically.