Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF). - Zhenghan Fang; Yong Chen; Mingxia Liu 001; Yiqiang Zhan; Weili Lin; Dinggang Shen (MLMI@MICCAI, 2018)

CNS: CycleGAN-Assisted Neonatal Segmentation Model for Cross-Datasets. - Jian Chen; Zhenghan Fang; Deqiang Xiao; Duc Toan Bui 001; Kim-Han Thung; Xianjun Li; Jian Yang 009; Weili Lin; Gang Li 001; Dinggang Shen; Li Wang 026 (GLMI@MICCAI, 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 (MICCAI (3), 2019)

Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting. - Zhenghan Fang; Yong Chen; Mingxia Liu 001; Lei Xiang; Qian Zhang 066; Qian Wang 001; Weili Lin; Dinggang Shen (IEEE Trans. Medical Imaging, 2019)

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)

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 001; Lei Xiang; Qian Zhang 066; Qian Wang 001; Weili Lin; Dinggang Shen (IEEE Trans. Medical Imaging, 2020)

Harmonized neonatal brain MR image segmentation model for cross-site datasets. - Jian Chen; Yue Sun; Zhenghan Fang; Weili Lin; Gang Li 001; Li Wang 026 (Biomed. Signal Process. Control., 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 001; He Zhang; Li Wang 026 (Comput. Medical Imaging Graph., 2021)

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 006; Charlie Androjna; Xin Yu; Dinggang Shen (MICCAI (6), 2022)

WaveSep: A Flexible Wavelet-Based Approach for Source Separation in Susceptibility Imaging. - Zhenghan Fang; Hyeong-Geol Shin; Peter C. M. van Zijl; Xu Li 003; Jeremias Sulam (MLCN@MICCAI, 2023)

DeepSTI: Towards tensor reconstruction using fewer orientations in susceptibility tensor imaging. - Zhenghan Fang; Kuo-Wei Lai; Peter C. M. van Zijl; Xu Li 003; Jeremias Sulam (Medical Image Anal., 2023)

Annotation-Efficient COVID-19 Pneumonia Lesion Segmentation Using Error-Aware Unified Semisupervised and Active Learning. - Zhenghan Fang; Junjie Bai; Xinyu Guo; Xin Wang 045; Feng Gao; Hao-Yu Yang; Bin Kong 001; Ying Hou; Kunlin Cao; Qi Song 001; Jun Xia 002; Youbing Yin (IEEE Trans. Artif. Intell., 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., 2023)

What's in a Prior? Learned Proximal Networks for Inverse Problems. - Zhenghan Fang; Sam Buchanan; Jeremias Sulam (ICLR, 2024)

Masked Conditional Diffusion Model for Enhancing Deepfake Detection. - Tiewen Chen; Shanmin Yang; Shu Hu 001; Zhenghan Fang; Ying Fu 003; Xi Wu 004; Xin Wang 045 (IJCNN, 2024)

ProxiMO: Proximal Multi-operator Networks for Quantitative Susceptibility Mapping. - Shmuel Orenstein; Zhenghan Fang; Hyeong-Geol Shin; Peter C. M. van Zijl; Xu Li 003; Jeremias Sulam (MLCN@MICCAI, 2024)

Towards Reliability MRAM for Energy-Efficient Spin-orbit Torque Switching. - Zhenghan Fang; Lirida Naviner; Wen Wang; Wei Le; Hao Cai 001 (SBCCI, 2024)

Image Deblurring Using Feedback Mechanism and Dual Gated Attention Network. - Jian Chen; Shilin Ye; Zhuwu Jiang; Zhenghan Fang (Neural Process. Lett., 2024)

A 40nm 4Mb High-Reliability STT-MRAM Achieving 18ns Write-Time and 94.9% Wafer-Level-Die-Yield Across -55°C-to-125°C. - Yaoru Hou; Haoran Du; Jiongzhe Su; Yibo Liu; Zhenghan Fang; Jia-Le Cui; Shuyu Wang; Chenxing Liu-Sun; Xuezhao Wu; Zhihua Xiao; Bo Liu 019; Xin Si; et al. (CICC, 2025)

Beyond Scores: Proximal Diffusion Models. - Zhenghan Fang; Mateo Díaz; Sam Buchanan; Jeremias Sulam (CoRR, 2025)