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eess.IV2026

Beyond the LUMIR challenge: The pathway to foundational registration models

Junyu Chen, Shuwen Wei, Joel Honkamaa +33

Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundati…

eess.IV2026

Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges

Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51

Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…

eess.IV2025

Physiological neural representation for personalised tracer kinetic parameter estimation from dynamic PET

Kartikay Tehlan, Thomas Wendler

Dynamic positron emission tomography (PET) with [F]FDG enables non-invasive quantification of glucose metabolism through kinetic analysis, often modelled by the two-tissue c…

eess.IV2025

Anatomy-constrained modelling of image-derived input functions in dynamic PET using multi-organ segmentation

Valentin Langer, Kartikay Tehlan, Thomas Wendler

Accurate kinetic analysis of [F]FDG distribution in dynamic positron emission tomography (PET) requires anatomically constrained modelling of image-derived input functions (…

eess.IV2024

Fine-Tuning TransMorph with Gradient Correlation for Anatomical Alignment

Lukas Förner, Kartikay Tehlan, Thomas Wendler

Unsupervised deep learning is a promising method in brain MRI registration to reduce the reliance on anatomical labels, while still achieving anatomically accurate transformations.…