Medical Image Registration

Overview

Medical image registration finds transformations that bring corresponding anatomy into alignment, enabling comparisons across time, modalities, or patients and supporting tasks such as motion correction and surgical guidance. Methods range from intensity- and feature-based optimization to deep networks, implicit deformation models, pretrained image features, and geometric or biomechanical priors; transformations may be rigid, affine, or deformable and diffeomorphic. Researchers evaluate these methods on settings such as brain MRI, lung CT, cardiac imaging, and intraoperative 2D–3D alignment, using landmarks, anatomical overlap, image similarity, and deformation quality. A central challenge is balancing accurate local matches with physically plausible, reliable deformations that generalize across scanners and modalities, since metrics can disagree and better overlap does not always mean better anatomical correspondence.

Latest papers

CardsList

96 papers17 papers in the last four weeks, up 55% on the four weeks before. 0.1% of all new papers.

  1. SHMoAReg: Spark Deformable Image Registration via Spatial Heterogeneous Mixture of Experts and Attention Heads

    Sep 24, 2025Yuxi Zheng, Jianhui Feng, Tianran Li +2Medical Image RegistrationMixture-of-Experts Models

  2. OncoReg: Medical Image Registration for Oncological Challenges

    Mar 29, 2025Wiebke Heyer, Yannic Elser, Lennart Berkel +15Medical Image RegistrationCross-Modal Image Registration

  3. UniReg: Conditional Unified Model for Medical Image Registration

    Mar 17, 2025Zi Li, Jianpeng Zhang, Tai Ma +7HealthcareMedical Image Registration

  4. SAMReg: SAM-enabled Image Registration with ROI-based Correspondence

    Oct 17, 2024Shiqi Huang, Tingfa Xu, Ziyi Shen +4Medical Image RegistrationDeformable Image Registration

  5. A Unified Deep Learning Framework for Motion Correction in Medical Imaging

    Sep 21, 2024Jian Wang, Razieh Faghihpirayesh, Danny Joca +2Fetal MRIMedical Image Registration

  6. Full-resolution MLPs Empower Medical Dense Prediction

    Nov 28, 2023Mingyuan Meng, Yuxin Xue, Dagan Feng +2Medical Image RegistrationMedical Image Segmentation