Zhenghan Fang

According to our database, Zhenghan Fang authored at least 17 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Image Deblurring Using Feedback Mechanism and Dual Gated Attention Network.

Jian Chen, Shilin Ye, Zhuwu Jiang, Zhenghan Fang

Neural Process. Lett., April, 2024

Towards Reliability MRAM for Energy-Efficient Spin-orbit Torque Switching.

Zhenghan Fang, Lirida Naviner, Wen Wang, Wei Le, Hao Cai

Proceedings of the 37th SBC/SBMicro/IEEE Symposium on Integrated Circuits and Systems Design, 2024

Masked Conditional Diffusion Model for Enhancing Deepfake Detection.

Tiewen Chen, Shanmin Yang, Shu Hu, Zhenghan Fang, Ying Fu, Xi Wu, Xin Wang

Proceedings of the International Joint Conference on Neural Networks, 2024

What's in a Prior? Learned Proximal Networks for Inverse Problems.

Zhenghan Fang, Sam Buchanan, Jeremias Sulam

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

LMSA-Net: A lightweight multi-scale aware network for retinal vessel segmentation.

Jian Chen, Jiaze Wan, Zhenghan Fang, Lifang Wei

Int. J. Imaging Syst. Technol., September, 2023

Annotation-Efficient COVID-19 Pneumonia Lesion Segmentation Using Error-Aware Unified Semisupervised and Active Learning.

Zhenghan Fang, Junjie Bai, Xinyu Guo, Xin Wang, Feng Gao, Hao-Yu Yang, Bin Kong, Ying Hou, Kunlin Cao, Qi Song, Jun Xia, Youbing Yin

IEEE Trans. Artif. Intell., April, 2023

DeepSTI: Towards tensor reconstruction using fewer orientations in susceptibility tensor imaging.

Zhenghan Fang, Kuo-Wei Lai, Peter C. M. van Zijl, Xu Li, Jeremias Sulam

Medical Image Anal., 2023

WaveSep: A Flexible Wavelet-Based Approach for Source Separation in Susceptibility Imaging.

Zhenghan Fang, Hyeong-Geol Shin, Peter C. M. van Zijl, Xu Li, Jeremias Sulam

Proceedings of the Machine Learning in Clinical Neuroimaging - 6th International Workshop, 2023

2022

Deep-Learning Based T₁ and T₂ Quantification from Undersampled Magnetic Resonance Fingerprinting Data to Track Tracer Kinetics in Small Laboratory Animals.

Yuning Gu, Yongsheng Pan, Zhenghan Fang, Jingyang Zhang, Peng Xue, Mianxin Liu, Yuran Zhu, Lei Ma, Charlie Androjna, Xin Yu, Dinggang Shen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Automatic brain extraction from 3D fetal MR image with deep learning-based multi-step framework.

Jian Chen, Zhenghan Fang, Guofu Zhang, Lei Ling, Gang Li, He Zhang, Li Wang

Comput. Medical Imaging Graph., 2021

Harmonized neonatal brain MR image segmentation model for cross-site datasets.

Jian Chen, Yue Sun, Zhenghan Fang, Weili Lin, Gang Li, Li Wang

Biomed. Signal Process. Control., 2021

2020

Erratum to "Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting".

Zhenghan Fang, Yong Chen, Mingxia Liu, Lei Xiang, Qian Zhang, Qian Wang, Weili Lin, Dinggang Shen

IEEE Trans. Medical Imaging, 2020

High-resolution 3D MR Fingerprinting using parallel imaging and deep learning.

Yong Chen, Zhenghan Fang, Sheng-Che Hung, Weitang Chang, Dinggang Shen, Weili Lin

NeuroImage, 2020

2019

Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting.

Zhenghan Fang, Yong Chen, Mingxia Liu, Lei Xiang, Qian Zhang, Qian Wang, Weili Lin, Dinggang Shen

IEEE Trans. Medical Imaging, 2019

RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Fingerprinting.

Zhenghan Fang, Yong Chen, Dong Nie, Weili Lin, Dinggang Shen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

CNS: CycleGAN-Assisted Neonatal Segmentation Model for Cross-Datasets.

Jian Chen, Zhenghan Fang, Deqiang Xiao, Duc Toan Bui, Kim-Han Thung, Xianjun Li, Jian Yang, Weili Lin, Gang Li, Dinggang Shen, Li Wang

Proceedings of the Graph Learning in Medical Imaging - First International Workshop, 2019

2018

Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF).

Zhenghan Fang, Yong Chen, Mingxia Liu, Yiqiang Zhan, Weili Lin, Dinggang Shen

Proceedings of the Machine Learning in Medical Imaging - 9th International Workshop, 2018