Abstract
This study was to explore the application value of magnetic resonance imaging (MRI) image reconstruction model based on complex convolutional neural network (CCNN) in the diagnosis and prognosis of cerebral infarction. Two image reconstruction methods, frequency domain reconstruction network (FDRN) and image domain reconstruction network (IDRN), were introduced based on the CCNN algorithm. In addition, they were integrated to form two new MRI image reconstruction models, namely D-FDRN and D-IDRN. The peak signal to noise ratio (PSNR) value and structural similarity index measure (SSIM) value of the image were compared and analyzed before and after the integration. The MRI images of patients with cerebral infarction in the dataset were undertaken as the data source, the average diffusion coefficient (DCavg) and apparent diffusion coefficient (ADC) values of different parts of the MRI image were measured, respectively. The correlation of the vein abnormality grading (VABG) to the infarct size and the degree of stenosis of the responsible vessel was analyzed in this study. The results showed that the PSNR and SSIM values of the MRI reconstructed image of the D-IDRN algorithm based on the CCNN algorithm in this study were higher than those of other algorithms. There was a positive correlation between the VABG and the infarct size (r = 0.48 and P = 0.002), and there was a positive correlation between the VABG the degree of stenosis of the responsible vessel (r = 0.58 and P < 0.0001). The ADC value of the central area of the infarct on the affected side was significantly greatly lower than that of the normal side (P < 0.01), and the DCavg value of the central area of the infarct was much lower in contrast to the normal side (P < 0.05). It indicated that an image reconstruction algorithm constructed in this study could improve the quality of MRI images. The ADC value and DCavg value changed in the infarct central area could be used as the basis for the diagnosis of cerebral infarction. If the vein was abnormal, the patient suffered from severe vascular stenosis, large infarction area, and poorer prognosis.
Funder
National Natural Science Foundation of China
Publisher
Public Library of Science (PLoS)
Reference22 articles.
1. Roles of astrocytes in cerebral infarction and related therapeutic strategies;J Ye;Zhejiang Da Xue Xue Bao Yi Xue Ban,2018
2. Clinical and Imaging Characteristics of Cerebral Infarction in Patients with Nonvalvular Atrial Fibrillation Combined with Cerebral Artery Stenosis;W Sun;J Atheroscler Thromb,2018
3. MRI of Cerebellar Infarction;LJ De Cocker;Eur Neurol,2017
4. Characterization of Brain Metabolism by Nuclear Magnetic Resonance;DP Downes;Chemphyschem,2019
5. Fast and robust segmentation of the striatum using deep convolutional neural networks;H Choi;J Neurosci Methods,2016
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