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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

OncoReg: Medical Image Registration for Oncological Challenges

Wiebke Heyer, Yannic Elser, Lennart Berkel +15

In modern cancer research, the vast volume of medical data generated is often underutilised due to challenges related to patient privacy. The OncoReg Challenge addresses this issue…

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

TotalRegistrator: Towards a Lightweight Foundation Model for CT Image Registration

Xuan Loc Pham, Gwendolyn Vuurberg, Marjan Doppen +12

Image registration is a fundamental technique in the analysis of longitudinal and multi-phase CT images within clinical practice. However, most existing methods are tailored for si…

eess.IV2025

Unstable Prompts, Unreliable Segmentations: A Challenge for Longitudinal Lesion Analysis

Niels Rocholl, Ewoud Smit, Mathias Prokop +1

Longitudinal lesion analysis is crucial for oncological care, yet automated tools often struggle with temporal consistency. While universal lesion segmentation models have advanced…

eess.IV2024

MRSegmentator: Multi-Modality Segmentation of 40 Classes in MRI and CT

Hartmut Häntze, Lina Xu, Christian J. Mertens +29

Purpose: To develop and evaluate a deep learning model for multi-organ segmentation of MRI scans. Materials and Methods: The model was trained on 1,200 manually annotated 3D axial…