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

机译:基于深度视觉信息感知和痴呆程度诱导的脑研发成像机制

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摘要

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.
机译:传统的医学图像识别方法受图像分辨率,图像亮度和颜色处理参数的限制,图像质量评估低。特别地,医学图像的不完全视觉信息和色彩结构紊乱使人类视觉感知和识别的复杂性显着增加,准确性差。为了解决上述问题,本文基于深脑信息感知和痴呆诱导脑磁共振成像(BMI-DVDI)的机制。一方面,基于视觉信息系统的深度融合,设计了高精度和低复杂性的医学图像深度视觉系统及其感知模型,用于医学图像质量的两个损害和视觉信息的看法。另一方面,痴呆模型通过痴呆图像信号的矩阵表示,痴呆症感测脑信号和图像重建的筛选设计。该模型有助于解决图像信号变形的问题,信号程度的测量精度和脑磁共振成像中的图像增强的重构。该模型提高了痴呆症等脑病的准确性。然后,我们将传感算法与大脑中的痴呆程度结合起来,并将其施加到大脑的MRI。最后,通过仿真实验和核磁共振成像实验,比较空间复杂性,时间复杂度,系统执行效率和图像质量评估。结果是该算法具有出色的性能。

著录项

  • 来源
    《Multimedia Tools and Applications》 |2019年第7期|8841-8859|共19页
  • 作者单位

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

    Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China|Mudanjiang Med Univ Hongqi Hosp Dept Endocrinol Mudanjiang Heilongjiang Peoples R China;

    Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China|Mudanjiang Med Univ Clin Coll 1 Mudanjiang Peoples R China;

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

    Mudanjiang Med Univ Hongqi Hosp Dept Neurol Mudanjiang Peoples R China|Heilongjiang Prov Key Lab Cerebral Ischem Stroke Mudanjiang Heilongjiang Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Brain MRI; Imaging; Deep visual information perception; Dementia degree induction;

    机译:脑MRI;成像;深度视觉信息感知;痴呆程度诱导;

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