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He Zhang 0023
Person information
Other persons with the same name
- He Zhang — disambiguation page
- He Zhang 0001
(aka: He Jason Zhang) — Nanjing University, Software Institute, State Key Laboratory of Novel Software Technology, China (and 3 more)
- He Zhang 0002
— Nanjing University of Science and Technology, School of Automation, China (and 1 more)
- He Zhang 0003
— Chinese Academy of Sciences, Institute of Semiconductors, State Key Laboratory on Integrated Optoelectronics, Beijing, China
- He Zhang 0004
— Adobe Inc., San Jose, CA, USA (and 1 more)
- He Zhang 0005
— Chinese Academy of Sciences, Institute of Atmospheric Physics, International Center for Climate and Environment Sciences, China
- He Zhang 0006
— Harbin Institute of Technology, Department of Electrical Engineering, China
- He Zhang 0007
— Xi'an Jiaotong University, School of Electronic and Information Engineering, China
- He Zhang 0008
— Chang'an University, Xi'an, China
- He Zhang 0009 — Aalto University, Helsinki, Finland
- He Zhang 0010
— Monash University, Faculty of Information Technology, Australia
- He Zhang 0011
— Beihang University, Fert Beijing Insitute, MIIT Key Laboratory of Spintronics, Beijing, China
- He Zhang 0012
— Monash University, Faculty of Information Technology, IT, Clayton, VIC, Australia
- He Zhang 0013
— University of Nottingham Ningbo China, Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, China (and 1 more)
- He Zhang 0014
- He Zhang 0015
- He Zhang 0016
- He Zhang 0017
- He Zhang 0018
- He Zhang 0019
- He Zhang 0020
- He Zhang 0021
- He Zhang 0022
- He Zhang 0024
- He Zhang 0025
- He Zhang 0026
- He Zhang 0027
- He Zhang 0028
- He Zhang 0029
- He Zhang 0030
- He Zhang 0031
- He Zhang 0032
- He Zhang 0033
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2020 – today
- 2025
- [j6]Jian Chen
, Mengting Guang, Geng Chen
, Xiong Yao, Tewodros Megabiaw Tassew, Zhen Li, Zuoyong Li, He Zhang:
NRD-Net: Non-local Residual Dense Network for Brain MR Image Super-Resolution. Int. J. Imaging Syst. Technol. 35(1) (2025) - 2024
- [j5]Jian Chen
, Ranlin Lu, Bin Jing, He Zhang, Geng Chen
, Dinggang Shen:
One model, two brains: Automatic fetal brain extraction from MR images of twins. Comput. Medical Imaging Graph. 112: 102330 (2024) - [j4]Wenhao Zhang
, Xin Zhang
, Lingyi Li, Lufan Liao, Fenqiang Zhao, Tao Zhong, Yuchen Pei
, Xiangmin Xu
, Chaoxiang Yang
, He Zhang
, Gang Li
:
A joint brain extraction and image quality assessment framework for fetal brain MRI slices. NeuroImage 290: 120560 (2024) - [j3]Shijie Huang
, Xukun Zhang
, Zhiming Cui
, He Zhang
, Geng Chen
, Dinggang Shen
:
Tissue Segmentation of Thick-Slice Fetal Brain MR Scans With Guidance From High-Quality Isotropic Volumes. IEEE Trans. Biomed. Eng. 71(4): 1404-1415 (2024) - [j2]Yuchen Pei
, Fenqiang Zhao
, Tao Zhong
, Laifa Ma, Lufan Liao, Zhengwang Wu, Li Wang
, He Zhang, Lisheng Wang
, Gang Li
:
PETS-Nets: Joint Pose Estimation and Tissue Segmentation of Fetal Brains Using Anatomy-Guided Networks. IEEE Trans. Medical Imaging 43(3): 1006-1017 (2024) - [c11]Yao Lv, Junpeng Tan, Shengxian Chen, He Zhang, Wenjun Cheng, Chaoxiang Yang, Xiangming Xu, Xin Zhang:
Two-Stage Implicit Representation Reconstruction with Iterative Registration and Double-Channel Encoder for Fetal MRI. ISBI 2024: 1-5 - [c10]Laifa Ma, Weili Lin, He Zhang, Gang Li:
Automated Fetal Brain Volume Reconstruction from Motion-Corrupted Stacks with Deep Learning. ISBI 2024: 1-5 - [c9]Xiuyu Dong, Zhengwang Wu, Laifa Ma, Ya Wang, Kaibo Tang
, He Zhang, Weili Lin, Gang Li:
Cycle-Consistent Learning for Fetal Cortical Surface Reconstruction. MICCAI (7) 2024: 212-222 - [c8]Junpeng Tan, Xin Zhang, Chunmei Qing, Chaoxiang Yang, He Zhang, Gang Li, Xiangmin Xu:
Fetal MRI Reconstruction by Global Diffusion and Consistent Implicit Representation. MICCAI (7) 2024: 329-339 - 2023
- [c7]Shijie Huang, Geng Chen
, Kaicong Sun, Zhiming Cui, Xukun Zhang, Peng Xue, Xuan Zhang, He Zhang, Dinggang Shen:
Super-Resolution Reconstruction of Fetal Brain MRI with Prior Anatomical Knowledge. IPMI 2023: 428-441 - [c6]Laifa Ma, Liangjun Chen, Fenqiang Zhao, Zhengwang Wu, Li Wang
, Weili Lin, He Zhang, Kenli Li, Gang Li:
Geometric Constrained Deep Learning for Motion Correction of Fetal Brain Mr Images. ISBI 2023: 1-5 - [c5]Shengxian Chen, Xin Zhang, Ruiyan Fang, Wenhao Zhang
, He Zhang, Chaoxiang Yang, Gang Li:
Dual-Stream Model with Brain Metrics and Images for MRI-Based Fetal Brain Age Estimation. MLMI@MICCAI (1) 2023: 424-433 - [i2]Shijie Huang, Xukun Zhang, Zhiming Cui, He Zhang, Geng Chen
, Dinggang Shen:
Tissue Segmentation of Thick-Slice Fetal Brain MR Scans with Guidance from High-Quality Isotropic Volumes. CoRR abs/2308.06762 (2023) - 2022
- [i1]He Zhang, Ran Zhang, Tao Zhou:
Learning high dimensional stochastic partial differential equations in a predictor-corrector framework. CoRR abs/2208.09883 (2022) - 2021
- [j1]Jian Chen
, Zhenghan Fang, Guofu Zhang, Lei Ling, Gang Li, He Zhang, Li Wang
:
Automatic brain extraction from 3D fetal MR image with deep learning-based multi-step framework. Comput. Medical Imaging Graph. 88: 101848 (2021) - [c4]Yuchen Pei
, Liangjun Chen, Fenqiang Zhao, Zhengwang Wu, Tao Zhong, Ya Wang, Changan Chen, Li Wang
, He Zhang, Lisheng Wang, Gang Li:
Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network. MICCAI (7) 2021: 239-248 - [c3]Xukun Zhang
, Zhiming Cui, Changan Chen, Jie Wei
, Jingjiao Lou, Wenxin Hu, He Zhang, Tao Zhou, Feng Shi
, Dinggang Shen:
Confidence-Aware Cascaded Network for Fetal Brain Segmentation on MR Images. MICCAI (3) 2021: 584-593 - 2020
- [c2]Lufan Liao, Xin Zhang, Fenqiang Zhao, Jingjiao Lou, Li Wang
, Xiangmin Xu, He Zhang, Gang Li:
Multi-Branch Deformable Convolutional Neural Network with Label Distribution Learning for Fetal Brain Age Prediction. ISBI 2020: 424-427 - [c1]Lufan Liao, Xin Zhang, Fenqiang Zhao, Tao Zhong, Yuchen Pei
, Xiangmin Xu, Li Wang
, He Zhang, Dinggang Shen, Gang Li:
Joint Image Quality Assessment and Brain Extraction of Fetal MRI Using Deep Learning. MICCAI (6) 2020: 415-424
Coauthor Index

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last updated on 2025-09-27 20:00 CEST by the dblp team
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