A novel GAN-based three-axis mutually supervised super-resolution reconstruction method for rectal cancer MR image.

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作者： Huiting,Zhang ^[1] ; Xiaotang,Yang ^[2] ; Yanfen,Cui ^[2] ; Qiang,Wang ^[3] ; Jumin,Zhao ^[4] ; Dengao,Li ^[5]

作者单位： College of Computer Science and Technology, Taiyuan University of Technology, Jinzhong 030600, China; Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province, Taiyuan 030024, China; Intelligent Perception Engineering Technology Centre of Shanxi, Jinzhong 030600, China. ^[1] Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan 030013, China. ^[2] College of Computer and Network Engineering, Shanxi Datong University, Datong 037009, China. ^[3] College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Jinzhong 030600, China; Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province, Taiyuan 030024, China; Intelligent Perception Engineering Technology Centre of Shanxi, Jinzhong 030600, China. ^[4] College of Computer Science and Technology, Taiyuan University of Technology, Jinzhong 030600, China; Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province, Taiyuan 030024, China; Intelligent Perception Engineering Technology Centre of Shanxi, Jinzhong 030600, China. Electronic address: lidengao@tyut.edu.cn. ^[5]

关键词 Depth information Generative Adversarial Networks Magnetic resonance image Rectal cancer Super-resolution Three-axis mutual supervision

主题词直肠肿瘤(Rectal Neoplasms);人类(Humans);磁共振成像(Magnetic Resonance Imaging);图像处理, 计算机辅助(Image Processing, Computer-Assisted);算法(Algorithms);图像解释, 计算机辅助(Image Interpretation, Computer-Assisted)

DOI 10.1016/j.cmpb.2024.108426

PMID 39368440

发布时间 2024-11-15

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