Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

The auto-segmentation of HCC using DL-AS provides perfect reproducibility, although it failed to detect 11.4% (4/35). However, the extracted parameters yielded different important predictors of MVI in HCC. Sphericity was a significant predictor in 2D DL-AS and 3D manual segmentation, while discrete compactness was a significant predictor in 2D manual segmentation.