姓名：舒畅

学历：博士

研究方向：医学图像配准

现工作单位：美团点评

2015年-2020年，中国科学院自动化研究所，计算机应用技术专业，博士。

2011年-2015年：华中科技大学，自动化专业，学士；

[1] Shu C, Xin T, Zhou F.X, Chen X and Han H. Dual Networks for High-Precision and High-Speed Registration of Brain Electron Microscopy Images[J]. Brain Sciences, 2020, 10(2): 86. (SCI, IF=3.332)

[2] Shu C, Chen X, Xie Q.W, Han H. An unsupervised network for fast microscopic image registration[C]//Medical Imaging 2018: Digital Pathology. SPIE, 2018: 363-370.

[3] Shu C, Chen X, Yu C, Han H. A Refined Spatial Transformer Network[C]// International Conference on Neural Information Processing (ICONIP). Springer, Cham, 2018:151-161.

[4] Shu C, Chen X, Xie Q.W, Xiao C, Han H. Non-iterative simultaneous rigid registration method for serial sections of biological tissue[C]//International Symposium on Biomedical Imaging (ISBI). IEEE, 2018: 436-440.

[5] Shu C, Li L.L, Li G.Q, Chen X, Han H. A Noniterative Simultaneous Rigid Registration Method for Serial Sections of Biological Tissues[J]. Applied Sciences, 2020,10(3): 1156. (SCI, IF=2.474)

[6] Wang H, Zhu Q, Ding L, Shen Y, Yang CY, Xu F, Shu C, Guo Y.J, Xiong Z.W, Shan Q.H, Jia F, Su P, Yang Q.R, Li B, Cheng Y.X, He X.B, Chen X, Wu F, Zhou J.N, Xu F.Q, Han H, Lau P.M, Bi G.Q. Scalable volumetric imaging for ultrahigh-speed brain mapping at synaptic resolution[J]. National Science Review, 2019, 6(5): 982-992. (SCI, IF=16.693)

[7] Yu C, Chen X, Yin L, Shu C, Zhao L, Han H. Image deformation based on contour using moving integral least squares[J]. IET Image Processing, 2018, 13(1): 152-160. (SCI, IF=2.004)

[8] Lv Y, Chen X, Shu C, Han H. Robust Global Optimized Affine Registration Method for Microscopic Images of Biological Tissue[C]//International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020: 1070-1074.

[9] Zhao L, Chen X, Shu C, Yu C, Han H. Real-time Image Deformation Using Locally weighted Moving Least Squares[C]// International Conference on Brain Inspired Cognitive Systems (BICS). Springer, Cham, 2018: 707-716.

[10] Yang M.K, Li G.Q, Shu C, Zhao P., Han H.GAN based Sample Simulation for SEM-Image Super Resolution[C]//CCF Chinese Conference on Computer Vision (CCCV). Springer, Singapore, 2017: 383-393.

[11] Xiao C, Liu J, Chen X, Han H, Shu C, Xie Q.W. Deep contextual residual network for electron microscopy image segmentation in connectomics[C]//International Symposium on Biomedical Imaging (ISBI). IEEE, 2018: 378-381.