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Yongfeng Yang
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2020 – today
- 2024
- [j19]Chang Wang, Yaning Ren, Rui Zhang, Chen Wang, Xiangying Ran, Jiefen Shen, Zongya Zhao, Wei Tao, Yongfeng Yang, Wenjie Ren, Yi Yu:
Schizophrenia classification and abnormalities reveal of brain region functional connection by deep-learning multiple sparsely connected network. Biomed. Signal Process. Control. 96: 106580 (2024) - [j18]Zhenxing Huang
, Wenbo Li
Accurate Whole-Brain Image Enhancement for Low-Dose Integrated PET/MR Imaging Through Spatial Brain Transformation. IEEE J. Biomed. Health Informatics 28(9): 5280-5289 (2024) - [j17]Wenjie Zhao
MMCA-NET: A Multimodal Cross Attention Transformer Network for Nasopharyngeal Carcinoma Tumor Segmentation Based on a Total-Body PET/CT System. IEEE J. Biomed. Health Informatics 28(9): 5447-5458 (2024) - [j16]Qiyang Zhang
Deep Generalized Learning Model for PET Image Reconstruction. IEEE Trans. Medical Imaging 43(1): 122-134 (2024) - [j15]Minghan Fu
OIF-Net: An Optical Flow Registration-Based PET/MR Cross-Modal Interactive Fusion Network for Low-Count Brain PET Image Denoising. IEEE Trans. Medical Imaging 43(4): 1554-1567 (2024) - [j14]Zhenguo Wang
Non-Invasive Quantification of the Brain [¹⁸F]FDG-PET Using Inferred Blood Input Function Learned From Total-Body Data With Physical Constraint. IEEE Trans. Medical Imaging 43(7): 2563-2573 (2024) - 2023
- [j13]Tong Sun
Cost-effective identification of the field maturity of tobacco leaves based on deep semi-supervised active learning and smartphone photograph. Comput. Electron. Agric. 215: 108373 (2023) - [j12]Minghan Fu
A Two-Branch Neural Network for Short-Axis PET Image Quality Enhancement. IEEE J. Biomed. Health Informatics 27(6): 2864-2875 (2023) - [c2]Tian Wang, Ning Zhou, Yongfeng Yang, Jingnan Li, Jiming Ma:
Research on Distribution Network Load Balancing Based on Regional Precise Regulation. iSPEC 2023: 1-6 - 2021
- [j11]Zhenxing Huang
FaNet: fast assessment network for the novel coronavirus (COVID-19) pneumonia based on 3D CT imaging and clinical symptoms. Appl. Intell. 51(5): 2838-2849 (2021) - [j10]Zhenxing Huang
Considering anatomical prior information for low-dose CT image enhancement using attribute-augmented Wasserstein generative adversarial networks. Neurocomputing 428: 104-115 (2021) - [j9]Zhenxing Huang
Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites. IEEE J. Biomed. Health Informatics 25(9): 3416-3427 (2021) - 2020
- [j8]Chao Fu
Dynamics analysis of a hollow-shaft rotor system with an open crack under model uncertainties. Commun. Nonlinear Sci. Numer. Simul. 83: 105102 (2020) - [j7]Qiyang Zhang
PET Image Reconstruction Using a Cascading Back-Projection Neural Network. IEEE J. Sel. Top. Signal Process. 14(6): 1100-1111 (2020) - [j6]Zhiyuan Huang, Zixiang Chen, Qiyang Zhang
CaGAN: A Cycle-Consistent Generative Adversarial Network With Attention for Low-Dose CT Imaging. IEEE Trans. Computational Imaging 6: 1203-1218 (2020)
2010 – 2019
- 2019
- [j5]Chao Fu
Steady-state response analysis of cracked rotors with uncertain‑but‑bounded parameters using a polynomial surrogate method. Commun. Nonlinear Sci. Numer. Simul. 68: 240-256 (2019) - [j4]Peijian Gu, Changhui Jiang, Min Ji
Low-Dose Computed Tomography Image Super-Resolution Reconstruction via Random Forests. Sensors 19(1): 207 (2019) - 2018
- [j3]Yongfeng Yang:
An English Translation Teaching Model Based on Interactive Reading Theory. Int. J. Emerg. Technol. Learn. 13(8): 146-158 (2018) - [c1]Dongmei Zhi, Xiaohong Ma
Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder. EMBC 2018: 558-561 - 2017
- [j2]Kuang Gong, Jian Zhou, Michel Tohme, Martin Judenhofer, Yongfeng Yang, Jinyi Qi
Sinogram Blurring Matrix Estimation From Point Sources Measurements With Rank-One Approximation for Fully 3-D PET. IEEE Trans. Medical Imaging 36(10): 2179-2188 (2017) - 2015
- [j1]Yongfeng Yang
Nonlinear response prediction of cracked rotor based on EMD. J. Frankl. Inst. 352(8): 3378-3393 (2015)
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