collaborators

5 papers

cs.CV2026

Inverse Bayesian Inference for Extracting Lesion Dynamics from Longitudinal Spectral CT

Lukas Förner, Melina Wördehoff, Julian Steffens +6

Longitudinal medical imaging captures temporal evolution of lesions, yet extracting the underlying dynamical parameters governing this evolution remains challenging. We propose an…

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…

cs.CV2026

Bridging MRI and PET physiology: Untangling complementarity through orthogonal representations

Sonja Adomeit, Kartikay Tehlan, Lukas Förner +7

Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modality-specific. Clarifying this di…

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.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.…