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% confidenceStandard bipartite matchers which rely on geometric proximity struggle when lesions appear, disappear, merge, or split
80% confidenceThis is the first approach to cast longitudinal lesion correspondence as a UOT problem, providing a principled alternative to distance-based bipartite matchers
80% confidenceThe proposed method produces interpretable lesion evolution graph with persistent, new, disappearing, merging, and splitting events without requiring heuristics or training data
80% confidenceUOT 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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