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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归纳的脑MRI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:传统医学图像识别方法受图像分辨率,图像亮度和色彩处理参数的限制,并且图像质量评价较低。尤其是医学图像视觉信息的不完整和色彩结构的混乱,使人类视觉感知和识别的复杂性大大提高,准确性较差。为了解决上述问题,本文基于深度脑信息知觉和痴呆诱发的脑磁共振成像(BMI-DVDI)的机制。一方面,基于视觉信息系统的深度融合,设计了一种医学图像深度视觉系统及其高精度,低复杂度的感知模型,以解决医学图像质量和视觉信息感知的两种损害。另一方面,痴呆模型是通过痴呆图像信号的矩阵表示,痴呆感测脑信号的筛选和图像重建等方法设计的。该模型有助于解决脑磁共振成像中图像信号变形,信号度测量精度以及图像增强重建等问题。该模型提高了诸如痴呆症等脑部疾病的准确性。然后,我们将传感算法与脑部痴呆程度相结合,并将其应用于脑部MRI。最后,通过仿真实验和核磁共振成像实验,比较了空间复杂度,时间复杂度,系统执行效率和图像质量评价。结果是该算法具有良好的性能。

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;深度视觉信息知觉;痴呆程度诱导;

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