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Symmetry-based representation for registration of multimodal images

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Abstract

We propose a new two-dimensional structural representation method for registration of multimodal images by using the local structural symmetry of images, which is similar at different modalities. The symmetry is measured in various orientations and the best is mapped and used for the representation image. The optimum performance is obtained when using only two different orientations, which is called binary dominant symmetry representation (BDSR). This representation is highly robust to noise and intensity non-uniformity. We also propose a new objective function based on L2 distance with low sensitivity to the overlapping region. Then, five different meta-heuristic algorithms are comparatively applied. Two of them have been used for the first time on image registration. BDSR remarkably outperforms the previous successful representations, such as entropy images, self-similarity context, and modality-independent local binary pattern, as well as mutual information-based registration, in terms of success rate, runtime, convergence error, and representation construction.

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Funding

This work received funding support from Babol Noshirvani University of Technology through grant program no. BNUT/389059/400.

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  1. Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran

    Mojtaba Soleimani, Ali Aghagolzadeh & Mehdi Ezoji

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  1. Mojtaba Soleimani
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  2. Ali Aghagolzadeh
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  3. Mehdi Ezoji
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Correspondence to Ali Aghagolzadeh.

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Soleimani, M., Aghagolzadeh, A. & Ezoji, M. Symmetry-based representation for registration of multimodal images. Med Biol Eng Comput 60, 1015–1032 (2022). https://doi.org/10.1007/s11517-022-02515-1

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  • DOI: https://doi.org/10.1007/s11517-022-02515-1

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