activity
20242026
collaborators

6 papers

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

Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence

Zhiyuan Li, Rongzhen Zhao, Wenyan Yang +3

The de facto approach in video object-centric learning maintains temporal consistency through learned dynamics modules that predict future object representations, called slots. We…

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…

cs.CV2025

New multimodal similarity measure for image registration via modeling local functional dependence with linear combination of learned basis functions

Joel Honkamaa, Pekka Marttinen

The deformable registration of images of different modalities, essential in many medical imaging applications, remains challenging. The main challenge is developing a robust measur…

cs.CV2025

Strategies for Robust Deep Learning Based Deformable Registration

Joel Honkamaa, Pekka Marttinen

Deep learning based deformable registration methods have become popular in recent years. However, their ability to generalize beyond training data distribution can be poor, signifi…

cs.LG2024

Identifiable causal inference with noisy treatment and no side information

Antti Pöllänen, Pekka Marttinen

In some causal inference scenarios, the treatment variable is measured inaccurately, for instance in epidemiology or econometrics. Failure to correct for the effect of this measure…