Application of CT Imaging in the Diagnosis of Cerebral Hemorrhage and Cerebral Infarction Nerve Damage

Yi, Xin; Hu, Chunhong; Yuan, Gang; Zhongchang, Miao; Yong-bao, Liu; Gu, Yushen

doi:10.1016/j.wneu.2020.02.007

Cited by 11 publications

(3 citation statements)

References 6 publications

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“…The brain is intolerant to ischemia and hypoxia. The blood supply interruption for 5 minutes will cause irreparable injury [ 12 ]. Imaging is an important part of the clinical diagnosis of ACI, and rapid and accurate diagnosis is a prerequisite for timely treatment [ 13 ].…”

Section: Discussionmentioning

confidence: 99%

Optimized Deconvolutional Algorithm‐based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

Chen

Bai

Shu

et al. 2022

Contrast Media & Molecular Imaging

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To apply deconvolution algorithm in computer tomography (CT) perfusion imaging of acute cerebral infarction (ACI), a convolutional neural network (CNN) algorithm was optimized first. RIU-Net was applied to segment CT image, and then equipped with SE module to enhance the feature extraction ability. Next, the BM3D algorithm, Dn CNN, and Cascaded CNN were compared for denoising effects. 80 patients with ACI were recruited and grouped for a retrospective analysis. The control group utilized the ordinary method, and the observation group utilized the algorithm proposed. The optimized model was utilized to extract the feature information of the patient’s CT images. The results showed that after the SE module pooling was added to the RIU-Net network, the utilization rate of the key features was raised. The specificity of patients in observation group was 98.7%, the accuracy was 93.7%, and the detected number was (1.6 ± 0.2). The specificity of patients in the control group was 93.2%, the accuracy was 87.6%, and the detected number was (1.3 ± 0.4). Obviously, the observation group was superior to the control group in all respects (P < 0.05). In conclusion, the optimized model demonstrates superb capabilities in image denoising and image segmentation. It can accurately extract the information to diagnose ACI, which is suggested clinically.

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Section: Discussionmentioning

confidence: 99%

Optimized Deconvolutional Algorithm‐based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

Chen

Bai

Shu

et al. 2022

Contrast Media & Molecular Imaging

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“… 1 Computerized tomography (CT) is a commonly used auxiliary method for the diagnosis of cerebral infarction, which is accurate and convenient. 2 Compared with conventional CT, spiral CT can perform volume scanning in a short period of time, reduce the artifacts caused by motion of patients, and significantly improve the spatial resolution and density resolution, so that early detection of diseased patients. 3 , 4 This review intends to briefly introduce the CT imaging features of cerebral infarction, to explore the effectiveness of the CT examination in promoting the physical function restoration.…”

Section: Introductionmentioning

confidence: 99%

Application of Quantitative CT Imaging in Rehabilitation Nursing of Cerebral Apoplexy Patients

2021

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Objectives: Electronic computed tomography (CT) is an important imaging method for the diagnosis of cerebral infarction. This paper explores the preventive effects of quantitative CT imaging and early rehabilitation nursing on patients with cerebral apoplexy and shoulder-hand syndrome. Methods: Sixty cerebral apoplexy patients treated were included as control group and given routine care from September 2018 to May 2020. Sixty cerebral apoplexy patients were included as observation group, and early rehabilitation nursing intervention was given based on control group. The incidence of shoulder-hand syndrome and upper limb function were compared between the two groups, to explore the effectiveness of the CT examination in promoting the physical function restoration. Results: The incidence of shoulder-hand syndrome in observation group after three months of intervention was lower than that in control group, and the severity was less than that in control group (P<0.05); The Ashworth score of muscle tension in observation group after three months of intervention was lower than that in control group, and the simplified FMA score of the upper limbs was higher than that in control group. Conclusion: Early rehabilitation nursing intervention after CT examination can prevent the occurrence of cerebral apoplexy and shoulder-hand syndrome and improve upper limb function, which is worthy of promotion. doi: https://doi.org/10.12669/pjms.37.6-WIT.4840 How to cite this:Yan B, Zhang H, Liu J. Application of Quantitative CT Imaging in Rehabilitation Nursing of Cerebral Apoplexy Patients. Pak J Med Sci. 2021;37(6):1574-1579. doi: https://doi.org/10.12669/pjms.37.6-WIT.4840 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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“…e images scanned by CT with the features of high resolution, clear pixels, and no artifacts can provide clear diagnostic evidence for the clinical treatment of patients. However, studies have found that plain CT examination is a means of examination with the highest radiation dose, and multiple CT scans will lead to an increase in radiation dose, which will have adverse effects on the health of patients [9,10]. erefore, the dose of scanning ray should be reduced as far as possible while not affecting the diagnosis of a cerebral hemorrhage.…”

Section: Introductionmentioning

confidence: 99%

Values of Sinogram Affirmed Iterative Reconstruction Algorithm-Based Low-Dose Computed Tomography Imaging in Clinical Diagnosis of Cerebral Hemorrhage

Wang

Chen

Fang

et al. 2021

Scientific Programming

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In this study, the sinogram affirmed iterative reconstruction (SAFIRE) technology combined with low-dose computed tomography (CT) scanning technology was applied to scan patients with cerebral hemorrhage to evaluate the application value of this combined technology in the diagnosis of patients with cerebral hemorrhage. 132 patients with cerebral hemorrhage admitted to the hospital were selected randomly as the research objects in this study. According to the patients’ wishes, all of them were rolled into an experimental group and a control group. Besides, patients who were willing to use low-dose CT imaging scanning technology based on the SAFIRE algorithm were classified into the experimental group, and those who received simple low-dose CT scans were classified into the control group. Subjective score, objective score (mean CT value), image noise (SD), signal-to-noise ratio (SNR), and contrast-noise ratio (CNR) were used to analyze and compare the two groups of detection methods. The results showed the following: (1) The average result of CT images was 4.05 ± 0.28 points for the control group and 4.43 ± 0.59 points for the experimental group. According to the classification, the excellent and good rates of the experimental group (89.9%) were markedly higher than the rates of the control group (65.8%), with a statistically obvious difference ( P < 0.05). (2) The standard deviation (SD), image signal-to-noise ratio (SNR), and contrast-noise ratio (CNR) results of gray matter, white matter, and cerebral hemorrhage lesions of patients from the experimental group were better than those of the control group, and the differences were statistically significant ( P < 0.05). In conclusion, the image quality of a low-dose CT scan reconstructed by the SAFIRE algorithm was superior to that of a simple low-dose CT scan. In other words, the image quality of CT images could be guaranteed by the SAFIRE technology under the condition of reducing radiation dose. It enabled patients with cerebral hemorrhage to carry out diagnostic examinations with guaranteed accuracy under the risk of low radiation and provided better imaging services for patients with cerebral hemorrhage.

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Application of CT Imaging in the Diagnosis of Cerebral Hemorrhage and Cerebral Infarction Nerve Damage

Cited by 11 publications

References 6 publications

Optimized Deconvolutional Algorithm‐based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

Optimized Deconvolutional Algorithm‐based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

Application of Quantitative CT Imaging in Rehabilitation Nursing of Cerebral Apoplexy Patients

Values of Sinogram Affirmed Iterative Reconstruction Algorithm-Based Low-Dose Computed Tomography Imaging in Clinical Diagnosis of Cerebral Hemorrhage

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