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20242026
most citedThe autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT $\unicode{x2013}$ Multitracer Multicenter Generalization

1 citations · 1 across the 1 of their papers we have counts for

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5 papers

cs.CV20261 cited

The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT $\unicode{x2013}$ Multitracer Multicenter Generalization

Jakob Dexl, Katharina Jeblick, Andreas Mittermeier +27

We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked automated lesion segmentation in whole-body PET/CT under a compositional generaliza…

cs.CV2025

MIMM-X: Disentangling Spurious Correlations for Medical Image Analysis

Louisa Fay, Hajer Reguigui, Bin Yang +2

Deep learning models can excel on medical tasks, yet often experience spurious correlations, known as shortcut learning, leading to poor generalization in new environments. Particu…

cs.CV2025

Retrospective motion correction in MRI using disentangled embeddings

Qi Wang, Veronika Ecker, Marcel Früh +2

Physiological motion can affect the diagnostic quality of magnetic resonance imaging (MRI). While various retrospective motion correction methods exist, many struggle to generalize…

eess.IV2025

TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI

Tugba Akinci D'Antonoli, Lucas K. Berger, Ashraya K. Indrakanti +16

Since the introduction of TotalSegmentator CT, there is demand for a similar robust automated MRI segmentation tool that can be applied across all MRI sequences and anatomic struct…

eess.IV2024

Highly efficient non-rigid registration in k-space with application to cardiac Magnetic Resonance Imaging

Aya Ghoul, Kerstin Hammernik, Andreas Lingg +4

In Magnetic Resonance Imaging (MRI), high temporal-resolved motion can be useful for image acquisition and reconstruction, MR-guided radiotherapy, dynamic contrast-enhancement, flo…