4.5 Article

Regional Localization of Mouse Brain Slices Based on Unified Modal Transformation

Journal

SYMMETRY-BASEL
Volume 13, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/sym13060929

Keywords

diffeomorphism; feature segmentation; modal transformation; multi-modal image registration; regional localization

Funding

  1. National Natural Science Foundation of China (NSFC) General Program [61807031]

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This study introduces a novel method based on the JEMI network to solve the issue of regional localization in brain science research. By converting the brain slice and ARA into a segmentation map with unified modality, the method effectively overcomes the influence of non-unified modal images and achieves accurate and rapid localization of the brain slice.
Brain science research often requires accurate localization and quantitative analysis of neuronal activity in different brain regions. The premise of related analysis is to determine the brain region of each site on the brain slice by referring to the Allen Reference Atlas (ARA), namely the regional localization of the brain slice. The image registration methodology can be used to solve the problem of regional localization. However, the conventional multi-modal image registration method is not satisfactory because of the complexity of modality between the brain slice and the ARA. Inspired by the idea that people can automatically ignore noise and establish correspondence based on key regions, we proposed a novel method known as the Joint Enhancement of Multimodal Information (JEMI) network, which is based on a symmetric encoder-decoder. In this way, the brain slice and the ARA are converted into a segmentation map with unified modality, which greatly reduces the difficulty of registration. Furthermore, combined with the diffeomorphic registration algorithm, the existing topological structure was preserved. The results indicate that, compared with the existing methods, the method proposed in this study can effectively overcome the influence of non-unified modal images and achieve accurate and rapid localization of the brain slice.

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