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

Qahqaie M, Neumann D, Heimann T, Maier A, Zimmer VA (2026)

Publication Language: English

Publication Status: Submitted

Publication Type: Conference contribution

Future Publication Type: Journal article

Publication year: 2026

Original Authors: Melika Qahqaie, Dominik Neumann, Tobias Heimann, Andreas Maier, Veronika A. Zimmer

Publisher: IEEE

Series: Proceedings - International Symposium on Biomedical Imaging

Book Volume: 2026-April

Conference Proceedings Title: 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)

Event location: London GB

ISBN: 9798331577636

DOI: 10.1109/ISBI61048.2026.11516053

Abstract

Evaluating lesion evolution in longitudinal CT scans of can cer patients is essential for assessing treatment response, yet establishing reliable lesion correspondence across time remains challenging. Standard bipartite matchers, which rely on geometric proximity, struggle when lesions appear, disappear, merge, or split. We propose a registration-aware matcher based on unbalanced optimal transport (UOT) that accommodates unequal lesion mass and adapts priors to patient-level tumor-load changes. Our transport cost blends (i) size-normalized geometry, (ii) local registration trust from the deformation-field Jacobian, and (iii) optional patch-level appearance consistency. The resulting transport plan is sparsified by relative pruning, yielding one-to-one matches as well as new, disappearing, merging, and splitting lesions without retraining or heuristic rules. On longitudinal CT data, our approach achieves consistently higher edge-detection precision and recall, improved lesion-state recall, and superior lesion-graph component F1 scores versus distance-only baselines.

Authors with CRIS profile

Melika Qahqaie Lehrstuhl für Informatik 5 (Mustererkennung) Dominik Neumann Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

How to cite

APA:

Qahqaie, M., Neumann, D., Heimann, T., Maier, A., & Zimmer, V.A. (2026). Unbalanced optimal transport for robust longitudinal lesion evolution with registration-aware and appearance-guided priors. In 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI). London, GB: IEEE.

MLA:

Qahqaie, Melika, et al. "Unbalanced optimal transport for robust longitudinal lesion evolution with registration-aware and appearance-guided priors." Proceedings of the 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), London IEEE, 2026.

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