Huizhong Ji, Zhili Zhang, Peng Xue, Meirong Ren, Enqing Dong
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引用次数: 0
Abstract
Purpose
Image registration is a critical component in medical image analysis applications. Optimization algorithms for energy functions play a crucial role in registration. Most registration methods improve the performance by modifying the energy function and optimizing it directly, neglecting the impact of the optimization algorithm. This paper is to investigate how to efficiently design an attention allocation strategy and improve the convergence of the optimization algorithm.
Methods
This paper introduces a novel image registration method that leverages the distributed alternating direction method of multipliers to perform optimization, named DADMMreg. Compared to the optimization algorithm using the alternating direction method of multipliers (ADMM), the optimization algorithm used in DADMMreg achieves better convergence by altering the optimization order of the similarity and regularization terms within the energy function. To overcome the limitations of intensity-based or structural-based similarity metrics, a modified structural similarity measure (SSIM) is proposed that takes into account both intensity and structural information. Considering that homogeneous smoothing prior at the sliding surface leads to inaccurate registration, a novel vector-modulus-based regularization metric is proposed to avoid physically implausible displacement fields.
Results
Experimental results on 4D-CT image dataset and COPD image dataset demonstrate the satisfactory registration performance of DADMMreg, with an average target registration error (TRE) of 0.9105 mm and 0.9201 mm, respectively. Meanwhile, the experimental results show that the DADMMreg method exhibits better convergence performance than other registration methods.
Conclusion
Compared to classical methods, the attention allocation strategy of DADMMreg enables faster convergence with comparable registration accuracy.
期刊介绍:
The purpose of Journal of Medical and Biological Engineering, JMBE, is committed to encouraging and providing the standard of biomedical engineering. The journal is devoted to publishing papers related to clinical engineering, biomedical signals, medical imaging, bio-informatics, tissue engineering, and so on. Other than the above articles, any contributions regarding hot issues and technological developments that help reach the purpose are also included.