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335 results on '"Wang, Chengjin"'

70. Additive Manufacturing in Vascular Stent Fabrication

Author

Yang Lei, Chen Xin, Zhang Lei, Li Lei, Kang Shuangzhu, Wang Chengjin, and Sun Wei

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

High-efficiency formation of personalized stent by additive manufacturing (3D printing) has gained deal of attention and research in interventional and personalized medicine. In this article, the structural characteristics of vascular scaffolds and the application and innovation of additive manufacturing technology in the process of angioplasty are reviewed. In the future, with the continuous maturity of additive manufacturing technology, it is expected to be an important part of interventional precision medicine to manufacture personalized vascular stent.

Published
2019
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74. Research on Assistant Diagnosis of Fundus Optic Neuropathy Based on Deep Learning.

Author

Wang, Chengjin, Zhang, Yuwei, Xu, Shuai, Liu, Yuyan, Xie, Lindan, Wu, Changlong, Yang, Qianhui, Chu, Yanhua, and Ye, Qing

Subjects
*DEEP learning, *ARTIFICIAL neural networks, *RESEARCH assistants, *ARTIFICIAL intelligence, *DIABETIC retinopathy, *IMAGE fusion, *OPTIC nerve diseases
Abstract

The purpose of this study was to use the neural network to distinguish optic edema (ODE), and optic atrophy from normal fundus images and try to use visualization to explain the artificial intelligence methods. Three hundred and sixty-seven images of ODE, 206 images of optic atrophy, and 231 images of normal fundus were used, which were provided by two hospitals. A set of image preprocessing and data enhancement methods were created and a variety of different neural network models, such as VGG16, VGG19, Inception V3, and 50-layer Deep Residual Learning (ResNet50) were used. The accuracy, recall, F1-score, and ROC curve under different networks were analyzed to evaluate the performance of models. Besides, CAM (class activation mapping) was utilized to find the focus of neural network and visualization of neural network with feature fusion. Our image preprocessing and data enhancement method significantly improved the accuracy of model performance by about 10%. Among the networks, VGG16 had the best effect, as the accuracy of ODE, optic atrophy and normal fundus were 98, 90, and 95%, respectively. The macro-average and micro-average of VGG16 both reached 0.98. From CAM we can clearly find out that the focus area of the network is near the optic cup. From feature fusion images, we can find out the difference between the three types fundus images. Through image preprocessing, data enhancement, and neural network training, we applied artificial intelligence to identify ophthalmic diseases, acquired the focus area through CAM, and identified the difference between the three ophthalmic diseases through neural network middle layers visualization. With the help of assistant diagnosis, ophthalmologists can evaluate cases more precisely and more clearly. [ABSTRACT FROM AUTHOR]

Published
2023
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93. Research on Invulnerability Evaluation of Optical Network Geography Disaster

Author

Wang Jingyu, Zhang Yinfa, Li Juan, and Wang Chengjin

Subjects
Index (economics), Network survivability, Assessment methods, Survivability, Graph theory, Network topology, Information science, Reliability engineering
Abstract

In view of the lack of an effective evaluation model for optical network survivability evaluation caused by geographical disasters, this paper has studied and proposed an evaluation model for optical network survivability considering geographical disasters, designed and proposed an evaluation index for survivability based on communication efficiency. On this basis, a survivability assessment method considering protection and unprotected conditions is proposed. Simulation results show that this method can effectively evaluate the invulnerability of optical networks under geographical disasters.

Published
2020

94. Forelimb joints contribute to locomotor performance in reindeer (Rangifer tarandus) by maintaining stability and storing energy

Author

Jianqiao Li, Cao Qingqiu, Hao Pang, Li Guoyu, Chen Wang, Guolong Yu, Wenchao Dong, Rui Zhang, Dianlei Han, Tao Li, Kong Lingxi, and Wang Chengjin

Subjects
musculoskeletal diseases, medicine.medical_specialty, 030310 physiology, lcsh:Medicine, Wrist, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Physical medicine and rehabilitation, Joint function, medicine, Biomechanics, Joint (geology), 030304 developmental biology, 0303 health sciences, General Neuroscience, Inverse dynamics, Work (physics), lcsh:R, General Medicine, Metacarpophalangeal joint, Gait, medicine.anatomical_structure, Forelimb, General Agricultural and Biological Sciences, Interphalangeal Joint, Geology, Locomotion, Reindeer
Abstract

Reindeer (Rangifer tarandus) have lengthy seasonal migrations on land and their feet possess excellent locomotor characteristics that can adapt to complex terrains. In this study, the kinematics and vertical ground reaction force (GRF) of reindeer forelimb joints (interphalangeal jointb, metacarpophalangeal jointc, and wrist jointd) under walk, trot 1, and trot 2 were measured using a motion tracking system and Footscan pressure plates. Significant differences among different locomotor activities were observed in the joint angles, but not in changes of the joint angles (αb,αc,αd) during the stance phase. Peak vertical GRF increased as locomotor speed increased. Net joint moment, power, and work at the forelimb joints were calculated via inverse dynamics. The peak joint moment and net joint power related to the vertical GRF increased as locomotor speed increased. The feet absorbed and generated more energy at the joints. During different locomotor activities, the contribution of work of the forelimbs changed with both gait and speed. In the stance phase, the metacarpophalangeal joint absorbed more energy than the other two joints while trotting and thus performed better in elastic energy storage. The joint angles changed very little (∼5°) from 0 to 75% of the stance phase, which reflected the stability of reindeer wrist joints. Compared to typical ungulates, reindeer toe joints are more stable and the stability and energy storage of forelimb joints contribute to locomotor performance in reindeer.

Published
2020

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