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  1. 1

    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

    Published 2025-02-01
    “…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 [email protected]: 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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  2. 2

    Evaluation of Learners’ Satisfaction with Open Flexible and Distance Learning Services at the University of Lagos Distance Learning Institute by Adenike Oladipo, Esther O. Oladele, Oladipupo Ajeyalemi, Folashade Afolabi, Peter O. Olayiwola, Johnson A. Adewara, Andrew Akala, Uchenna Udeani

    Published 2024-12-01
    “…En outre, les diplômés de DLI sont légèrement satisfaits du processus d'achèvement du programme tel que le traitement des résultats et la convocation avec des réponses moyennes de 7,74 et 7,44, mais insatisfaits des toilettes avec une moyenne de 5,02. …”
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