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Brain MRI imaging mechanism based on deep visual information perception and dementia degree induction

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Abstract

The traditional medical image recognition methods are limited by image resolution, image brightness and color processing parameters, and image quality evaluation is low. In particular, the incomplete visual information of medical images and the disorder of color structure make the complexity of human visual perception and recognition significantly increased and the accuracy is poor. In order to solve the above problems, this paper is based on the mechanism of deep brain information perception and dementia induced brain magnetic resonance imaging (BMI-DVDI). On the one hand, based on the depth fusion of the visual information system, the medical image depth vision system and its perception model with high precision and low complexity are designed for the two damage of medical image quality and the perception of visual information. On the other hand, the dementia model is designed by means of matrix representation of dementia image signal, screening of dementia sensing brain signal and image reconstruction. The model is helpful to solve the problems of image signal deformation, measurement precision of signal degree and reconstruction of image enhancement in brain magnetic resonance imaging. This model enhances the accuracy of brain diseases such as dementia. Then, we combine the sensing algorithm with the degree of dementia in the brain, and apply it to the MRI of the brain. Finally, through simulation experiments and nuclear magnetic resonance imaging experiments, the space complexity, time complexity, system execution efficiency and image quality evaluation are compared. The result is that the proposed algorithm has excellent performance.

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Acknowledgements

This work is supported in part by National Natural Science Foundation of China (81771795), Scientific research project of the health planning committee of Heilongjiang (2017-337), Scientific research project of Mudanjiang Municipal Science and Technology Bureau (Z2016s0066), and Graduate Innovation fund project of Mudanjiang Medical University (2017YJSCX-05MY).

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Authors and Affiliations

  1. Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China

    Jiayuan Ding, Zihe Jiang, Yuexin Zhao, Xue Wang, Mengfei He, Weina Zhao & Changhao Yin

  2. Heilongjiang Provincial Key Laboratory of Cerebral Ischemic Stroke Prevention and Control, Heilongjiang, China

    Jiayuan Ding, Siou Li, Zhilong Wang, Zihe Jiang, Yuexin Zhao, Xue Wang, Mengfei He, Weina Zhao & Changhao Yin

  3. Department of Endocrinology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Heilongjiang, China

    Siou Li

  4. First Clinical College of Mudanjiang Medical University, Mudanjiang, China

    Zhilong Wang

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  1. Jiayuan Ding
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  2. Siou Li
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  3. Zhilong Wang
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  4. Zihe Jiang
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  5. Yuexin Zhao
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  6. Xue Wang
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  7. Mengfei He
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  8. Weina Zhao
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  9. Changhao Yin
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Correspondence to Changhao Yin.

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Ding, J., Li, S., Wang, Z. et al. Brain MRI imaging mechanism based on deep visual information perception and dementia degree induction. Multimed Tools Appl 78, 8841–8859 (2019). https://doi.org/10.1007/s11042-018-6506-3

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  • DOI: https://doi.org/10.1007/s11042-018-6506-3

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