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Comprehensive landscape and oncogenic role of extrachromosomal circular DNA in malignant biliary strictures by Zhuo Cheng, Xuanmei Luo, Wenzheng Liu, Xiaofang Lu, Hong Chang, Yingchun Wang, Wei Zheng, Xiue Yan, Yonghui Huang

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MYH9 promotes malignant progression of glioma cells through regulating β-catenin stability via epithelial-mesenchymal transition signaling pathway by Zigui Chen, Chao Liu, Wei Zheng, Zhilong Li, Yuanhui Tang, Jun Peng, Changfeng Miao, Dandan Zheng, Ying Xia

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Real-time holographic camera for obtaining real 3D scene hologram by Zhao-Song Li, Chao Liu, Xiao-Wei Li, Yi Zheng, Qian Huang, Yi-Wei Zheng, Ye-Hao Hou, Chen-Liang Chang, Da-Wei Zhang, Song-Lin Zhuang, Di Wang, Qiong-Hua Wang

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Investigating the Use of Generative Adversarial Networks-Based Deep Learning for Reducing Motion Artifacts in Cardiac Magnetic Resonance by Ma ZP, Zhu YM, Zhang XD, Zhao YX, Zheng W, Yuan SR, Li GY, Zhang TL

“…Ze-Peng Ma,1,2,* Yue-Ming Zhu,3,* Xiao-Dan Zhang,4 Yong-Xia Zhao,1 Wei Zheng,3 Shuang-Rui Yuan,1 Gao-Yang Li,1 Tian-Le Zhang1 1Department of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, People’s Republic of China; 2Hebei Key Laboratory of Precise Imaging of inflammation Tumors, Baoding, Hebei Province, 071000, People’s Republic of China; 3College of Electronic and Information Engineering, Hebei University, Baoding, Hebei Province, 071002, People’s Republic of China; 4Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiao-Dan Zhang, Department of Ultrasound, Affiliated Hospital of Hebei University, No. 212 of Yuhua East Road, Lianchi District, Baoding, 071000, People’s Republic of China, Tel +86 17325535302, Email xiaodanzhangzxd@126.comObjective: To evaluate the effectiveness of deep learning technology based on generative adversarial networks (GANs) in reducing motion artifacts in cardiac magnetic resonance (CMR) cine sequences.Methods: The training and testing datasets consisted of 2000 and 200 pairs of clear and blurry images, respectively, acquired through simulated motion artifacts in CMR cine sequences. …”
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