磁共振成像
图像配准
强度(物理)
计算机视觉
人工智能
运动(物理)
计算机科学
核磁共振
物理
放射科
医学
光学
图像(数学)
作者
Haizhou Liu,Yijia Zheng,Zhou Liu,Yuxi Jin,Zhihua Li,Jidong Han,Ziang Di,Hairong Zheng,Dong Liang,Yin Wu,Dehong Luo,Zhanli Hu
标识
DOI:10.1109/jbhi.2025.3574356
摘要
Physiological and external motion cause inter-frame misalignment in chemical exchange saturation transfer magnetic resonance imaging (CEST-MRI), thereby compromising quantitative accuracy. In CEST-MRI, saturation effects induce intensity variations, resulting in motion-intensity coupling that makes registration particularly challenging. To address this issue, we extend the finite element digital image correlation (FE-DIC) framework by introducing an alternating correction strategy that iteratively refines both motion and intensity estimation. Unlike conventional FE-DIC approaches that assume intensity constancy, the proposed method incorporates mechanical regularization to suppress non-physical deformations, alongside intensity correction to compensate for reference-target contrast discrepancies. This mutual reinforcement enables progressively improved registration across the CEST sequence. The robustness and effectiveness of the method were evaluated on three datasets. In simulated liver data, it maintains RMSE within 0.4 pixels, reducing error by 0.5 pixels compared to RPCA & PCA (a PCA-based synthetic reference generation method for CEST registration). On clinical brain and pig cardiac data, it achieves average SSIM of 0.83, outperforming RPCA & PCA by 0.03 and surpassing CNN-based registration (e.g., AirLab) by 0.10. The consistent results across datasets highlight its generalizability, making it a promising tool for metabolic quantification in clinical and research settings.
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