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

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.