Deformable Medical Image Registration with Effective Anatomical Structure Representation and Divide-and-Conquer Network

Ma X. Pan Y. Zeng Q. Lu M. Yerzhanuly B.M. Matkerim B. Xia Y.
2025 Institute of Electrical and Electronics Engineers Inc.

IEEE Journal of Biomedical and Health Informatics
2025

Effective representation of Regions of Interest (ROI) and independent alignment of these ROIs can significantly enhance the performance of deformable medical image registration (DMIR). However, current learning-based DMIR methods have limitations. Unsupervised techniques disregard ROI representation and proceed directly with aligning pairs of images, while weakly-supervised methods heavily depend on label constraints to facilitate registration. To address these issues, we introduce a weakly-supervised ROI-based registration approach named EASR-DCN. Our method represents medical images through effective ROIs and achieves independent alignment of these ROIs without requiring labels. Specifically, we first used a Gaussian mixture model for intensity analysis to represent images using multiple effective ROIs with distinct intensities. Furthermore, we propose a novel Divide-and-Conquer Network (DCN) that processes ROIs through separate channels to independently align their features. The resulting sub-deformation fields are seamlessly integrated to generate a comprehensive displacement vector field. Extensive experiments were performed on three MRI and one CT datasets to showcase the superior accuracy and deformation reduction efficacy of our EASR-DCN. Compared to VoxelMorph, our EASR-DCN achieved improvements of 10.31% in the Dice score for brain MRI, 13.01% for cardiac MRI, and 5.75% for hippocampus MRI, highlighting its promising potential for clinical applications.

Feature Alignment , Image Registration , Representation Learning , Weakly supervised Learning

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Northwestern Polytechnical University, National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, School of Computer Science and Engineering, Xian, 710072, China
Northwestern Polytechnical University, Kazakhstan
Al-Farabi Kazakh National University, Almaty, 050040, Kazakhstan

Northwestern Polytechnical University
Northwestern Polytechnical University
Al-Farabi Kazakh National University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026