Research Advancement and Application Exploration of Coronary CT Angiography-derived Fractional Flow ReserveZOU Limiao, XU Cheng, WANG Yining1-6
Applications and Challenges of Artificial-intelligence-based Image Reconstruction in Clinical Computed Tomography ImagingZHANG Zhijie, NIU Yantao, WANG Zhenchang7-14
CT Image Metal Artifact Reduction Based on Deep LearningYE Zihao, JIN Tong, CHE Zigang, WANG Shisen, LIU Jin, CHEN Yang15-27
Clinical Research Progress on Deep Learning for Metal Artifact Reduction in Computed Tomography ImagesLIU Xiangcheng, HUANG Xiaoying, WEI Pengyue, WANG Pengchao, GUO Fangkai, BAO Yunfeng28-35
Photon-counting CT Projection Denoising Method Based on Optimal Transport NetworkLI Siyu, LIANG Ningning, ZHENG Zhizhong, CAI Ailong, LI Lei, YAN Bin36-47
Enhanced Restormer for Low-dose CT Image Reconstruction Based on Multi-attention FusionWU Songwen, FANG Chenyun, QIAO Zhiwei48-57
Quantitative Precision and Noise Reduction Efficacy of Deep Learning Reconstruction Algorithms in 60-kVp Ultra-low Tube Voltage Computed Tomography:A Phantom StudyCAO Boxuan, BIAN Zhaoying, HU Zhi, LIU En, CUI Qi, WEN Ge, ZHOU Jianwei, MA Jianhua, WANG Hao, ZENG Dong58-66
Influence of ClearInfinity Algorithm Weight on the Quality of Virtual Monoenergetic Images in Cranial Spectral Computed Tomography AngiographyXU Jun, HUANG Yihao, LIU Zhiwei, LI Changwei, BAI Xue, NING Xianying, HU Xiaoli, LUO Kun, WU Hongying, KONG Xiangchuang67-73
Deep Learning Reconstruction for Ultra-high-resolution Cranial CT:Image Quality Enhancement and Radiation Dose ReductionYANG Jiashuo, CHENG Yuhe, MA Zixuan, LIU Dandan, ZHANG Yongxian74-79
The Impact of Deep Learning Reconstruction Algorithm Combined with Ultra-high Resolution Detector on Orbital CT Image QualityZHAO Yiang, CHENG Yuhe, MA Zixuan, ZHANG Yongxian, LIU Dandan80-85