波谱学杂志2024，Vol.41Issue(4)：454-468,15.DOI:10.11938/cjmr20243110
用于超快时空编码MRI的Transformer超分辨率重建算法研究
Research on Transformer Super-Resolution Reconstruction Algorithm for Ultrafast Spatiotemporal Encoding Magnetic Resonance Imaging
摘要
Abstract
Spatio-temporal encoding(SPEN)magnetic resonance imaging(MRI)is an ultrafast MRI technique.However,resolution of the original image acquired with SPEN is relatively low,requiring super-resolution reconstruction based on sequence physics principles to improve spatial resolution.As the existing SPEN super-resolution reconstruction algorithms based on deep learning have confined abilities to capture long-range dependencies,this paper proposes a transformer-based SPEN MRI super-resolution reconstruction algorithm.An encoder-decoder structure is adopted,and a transformer module is introduced to extract local context information and long-range dependencies of feature maps.Experimental results show that the proposed reconstruction method can reconstruct a super-resolution image with high spatial resolution and no aliasing artifacts from the low-resolution SPEN image without adding additional sampling points.Compared to the existing super-resolution methods,the proposed method achieves better results on both clinical and preclinical datasets.关键词
超快磁共振成像/时空编码/深度学习/超分辨率/图像重建Key words
ultrafast MRI/spatio-temporal encoding(SPEN)/deep learning/super-resolution/image reconstruction分类
数理科学引用本文复制引用
宁欣宙,黄臻,陈西曲,刘鑫杰,陈罡,张志,鲍庆嘉,刘朝阳..用于超快时空编码MRI的Transformer超分辨率重建算法研究[J].波谱学杂志,2024,41(4):454-468,15.基金项目
国家重点研发计划(2023YFE0113300,2022YFF0707000) （2023YFE0113300,2022YFF0707000）
国家自然科学基金项目(22327901) （22327901）
中国科学院B类战略性先导科技专项(XDB0540300) （XDB0540300）
湖北省科技创新人才及服务专项(2023EHA003) （2023EHA003）
中国科学院磁共振技术联盟科研仪器设备研制项目(2021GZL001) （2021GZL001）
中国科学院精密测量科学与技术创新研究院交叉培养项目(S21S4101) （S21S4101）
中国科学院科研仪器开发项目(YJKYYQ 20190032). （YJKYYQ 20190032）
