SOURCE-LINKED INTELLIGENCE
Low-Rank Velocity Fields as a Structural Prior for Unsupervised 4D Medical Image Interpolation
Endpoint-only unsupervised 4D medical image interpolation synthesizes intermediate volumes from sparsely sampled sequences with only the start and end volumes available for training; however, this weakly constrained setting often yields intermediates with unstable boundaries and non-physiological motion, limiting interpretability and downstream analysis. We propose low-rank velocity fields as a structural prior, constraining motion to a structured Tucker low-rank velocity field space that decomposes motion into globally shared spatial bases and a compact sample-specific core, thereby encouragi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T03:30:03.000Z
First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.