Medical imaging technology shock and volatility of macro economics: Analysis using a three-sector dynamical stochastic general equilibrium REC model

2017 ◽  
Vol 25 (4) ◽  
pp. 689-700
Author(s):  
Shurong Han ◽  
Yeqing Huang
Keyword(s):  
Medical Imaging ◽  
General Equilibrium ◽  
Imaging Technology ◽  
Technology Shock ◽  
Economics Analysis

scholarly journals Denosing CT/MRI Images Restoration using Radial Basis Function Neural Network

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1364-1369
Keyword(s):  
Neural Network ◽  
Medical Imaging ◽  
Image Restoration ◽  
Radial Basis Function ◽  
Image Denoising ◽  
Basis Function ◽  
Medical Examination ◽  
Imaging Technology ◽  
Large Numbers ◽  
Original Domain

Medical imaging technology is becoming an important component of large numbers of applications such as diagnosis, treatment, survey and medical examination. Image restoration manages conveying back the bended image to its original domain. It re-establishes the corrupted image into keener image. This paper centers around evacuation of noise strategies in medical images with denoising a point by point overview has been completed on various image denoising methods and their exhibitions were evaluated and it is an activity to examine and evaluate various variations of denoising methods to enhance their execution and visual standard.

Application of Adaptive Threshold Image Segmentation Algorithm in Orthopedic CT Imaging

2019 ◽  
Vol 9 (8) ◽  
pp. 1736-1740
Author(s):  
Fuqin Bao ◽  
Dapeng Wang ◽  
Hongyan Zhao ◽  
Bo Xu
Keyword(s):  
Image Segmentation ◽  
Medical Imaging ◽  
Adaptive Threshold ◽  
Control Group ◽  
Observation Group ◽  
Trauma Recovery ◽  
Actual Problem ◽  
Imaging Technology ◽  
Bone Trauma ◽  
Orthopedic Care

Objective: To explore the application and analysis of image segmentation in the rehabilitation of patients with bone trauma during orthopedic nursing. Methods: Sixty patients with orthopedic trauma in our hospital were enrolled. The patients were divided into observation group and control group by four weeks. The control group was the traditional observation image, and the observation group was analyzed by image segmentation technology. Therefore, the two groups of patients are provided with nursing treatment, and finally, the progress of bone trauma recovery is periodically observed. Results: The degree of recovery in the observation group was 43% in the four-week period and 30% in the control group. It can be seen that the adaptive threshold algorithm makes orthopedic care more effective in image segmentation. Discussion: In medical imaging technology, different imaging devices can provide a variety of voxel information. The bone morphology information provided by CT images can make orthopedic care more targeted. Conclusion: Image segmentation technology provides a reliable predictive treatment solution in the nursing work, which solves the actual problem of the patient in the injury and the disease, so that the patient can recover faster. However, the expected research results of medical imaging technology research have guiding significance for the doctor's clinical diagnosis and preoperative and postoperative planning.

Diagnosis of Neuropathy of Cervical Posterior Longitudinal Ligament by Medical Imaging Technology

2020 ◽  
Vol 10 (9) ◽  
pp. 2084-2089
Author(s):  
Cheng Yang ◽  
Liguo Wang ◽  
Guijiang Wang ◽  
Bortolotti Paolo
Keyword(s):  
Cervical Spine ◽  
Medical Imaging ◽  
Evaluation Method ◽  
Clinical Manifestations ◽  
Posterior Longitudinal Ligament ◽  
Lower Limbs ◽  
Sensory Loss ◽  
Imaging Technology ◽  
International Orthopaedic ◽  
Selection Of

The patients were evaluated by the International Orthopaedic Association evaluation method and graded and correlated by medical imaging technology. The results showed that 41% of the patients had unstable gait and sensory loss of lower limbs or muscle weakness in the analysis of clinical manifestations. In the analysis of therapeutic effect by using medical imaging technology, it was found that the patients’ scores increased significantly after operation, which was significantly different from those before operation (P < 0.01). There was a significant correlation between preoperative scores and imaging changes, but no significant correlation between other indicators after surgery. Therefore, through the study, it is found that the application of medical imaging technology in the observation and treatment of ossification of the posterior longitudinal ligament of cervical spine can play a very positive and accurate role in the analysis of the patient’s condition, and provide an experimental basis for the selection of treatment methods for ossification of the posterior longitudinal ligament of cervical spine and the application direction of medical imaging technology.

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