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Peer-reviewed paperarXiv

Unbalanced optimal transport for robust longitudinal lesion evolution with registration-aware and appearance-guided priors

View original at arxiv.org
{ "id": "2602.09933v1", "url": "http://arxiv.org/abs/2602.09933v1", "title": "Unbalanced optimal transport for robust longitudinal lesion evolution with registration-aware and appearance-guided priors", "summary": "Evaluating lesion evolution in longitudinal CT scans of can cer patients is essential for assessing treat…
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  • Accurate detection of merging and splitting lesions is crucial for reliable response evaluation, as overlooking these events can lead to misclassification under RECIST and potentially incorrect assessment of disease progression

    80% confidence
  • Standard bipartite matchers which rely on geometric proximity struggle when lesions appear, disappear, merge, or split

    80% confidence
  • This is the first approach to cast longitudinal lesion correspondence as a UOT problem, providing a principled alternative to distance-based bipartite matchers

    80% confidence
  • The proposed method produces interpretable lesion evolution graph with persistent, new, disappearing, merging, and splitting events without requiring heuristics or training data

    80% confidence
  • UOT achieves consistently higher edge-detection precision and recall, improved lesion-state recall, and superior lesion-graph component F1 scores versus distance-only baselines

    80% confidence

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