arXiv AI
LiFUSE: Frequency-Spatial Unified Self-Supervised Pretraining for Liver Disease Analysis on Non-contrast CT
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LiFUSE: Frequency-Spatial Unified Self-Supervised Pretraining for Liver Disease Analysis on Non-contrast CT
LiFUSE introduces a unified frequency‑spatial self‑supervised pretraining framework for liver disease analysis on non‑contrast CT scans. The method employs a frequency branch that uses random band‑stop masking and spectrum reconstruction, and a spatial branch that performs hybrid‑granularity masked volumetric reconstruction, with a cross‑domain consistency scheme to fuse the two branches. Experiments on three clinical tasks and a public transfer setting demonstrate that LiFUSE consistently outperforms strong baselines, indicating its potential to enhance liver disease screening using low‑contrast NCCT images.
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