论文：
Guoqing Wu#, Shun Yao#, Xiaohai Liu, Wenting Rui, Hanning Xu, Zengyi Ma, Yongfei Wang, Zhenwei Yao, Ge Chen, Ying Guo, Haiyong He, Nidan Qiao ,Jinhua Yu* ,Yao Zhao*. Generative adversarial networks-based Image-to-Image translation allows tumor consistency prediction from standard MR images in pituitary adenomas. PLOS Digital Health. 2026.5(5): e0001407.
Shuai Wang, Hao Wang, Ye Tang, Jixian Lin, Jinhua Yu*, Guoqing Wu*. Masked pre-training and pseudo-vessel enhancement-based semi-supervised cerebral vascular segmentation. Medical Physics.2026. 53:e70440.
Yifan Chen, Nidan Qiao, Xinyuan Niu, Yao Zhao, Jinhua Yu, Guoqing Wu*, Haixia Cheng*. Diffusion-based virtual multi-stain staining for pituitary adenoma histopathology. Computerized Medical Imaging and Graphics. 2026.129:102723.
Guoqing Wu#, Zehang Ning#, Xiaorong Yan, Jianfang Li, Chiyuan Ma, Haixia Cheng, Zixiang Cong, Junjun Li, Shengyu Sun, Yongfei Wang, Xingli Deng, Changzhen Jiang, Hong Chen, Hui Ma, Jinhua Yu*, Yao Zhao*, Nidan Qiao*. Deep Learning based Semi-automated Model can Predict Lineage in Patients with Pituitary Neuroendocrine Tumors. Acta Neuropathologica Communications. 2025.9.
Yuan Zheng, Shujun Xia, Zhao Yao, Jianqiao Zhou*, Jinhua Yu*, Guoqing Wu*. Integrating intratumor-peritumor implicit correlation and deep semantic features for ultrasound breast cancer diagnosis. Biomedical Signal Processing and Control. 2025.3
Zehang Ning#; Bojie Yang#; Yuanyuan Wang; Zhifeng Shi; Jinhua Yu*; Guoqing Wu*; Dual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma, Computer Methods and Programs in Biomedicine, 2024, 261,108580
Shiwen Cao, Zhaoyu Hu, Xuan Xie, Yuanyuan Wang, Jinhua Yu, Bojie Yang, Zhifeng Shi, Guoqing Wu*, Integrated diagnosis of glioma based on magnetic resonance images with incomplete ground truth labels, Computers in Biology and Medicine,2024,180,108968.
Guoqing Wu, Hao Wang, Xiaojun Ma, et al., SWI and CTP fusion model based on sparse representation method to predict cerebral infarction trend. Frontiers in Neuroscience. 2024, 18:1360459.
Guoqing Wu, Zhifeng Shi, Zeyang Li, et al., Study of radiochemotherapy decision-making for young highrisk low-grade glioma patients using a macroscopic and microscopic combined radiomics model, European Radiology, 2023, 18(3): 1-12
Nidan Qiao#, Damin Yu#, Guoqing Wu#, et al., Low-rank fusion convolutional neural network for predictionof remission after stereotactic radiosurgery in patients with acromegaly: a proof-of-concept study. Journal of Pathology，2022, 258(1):49-57.
Wu Guoqing, Chen Xi, Shi Zhifeng, et al.,Convolutional neural network with coarse-to-fine resolution fusion and residual learning structures for cross-modality image synthesis. Biomedical Signal Processing and Control,2022,Volume 71, Part B.
Wu Guoqing#, Jiang Zhaoshun#, Cai Yuxi, et al. Multi-order brain functional Connectivity network-based Machine learning method for Recognition of delayed Neurocognitive recovery in older Adults undergoing non-cardiac Surgery. Frontiers in Neuroscience,2021:1-13.
Xiong Siyu#, Wu Guoqing#, Fan Xitian, et al. MRI‑based brain tumor segmentation using FPGA‑accelerated neural network. BMC Bioinformatics,2021:1-15.
Wu Guoqing#, Chen Xi#, Lin Jixian#, et al. Identification of invisible ischemic stroke in noncontrast CT based on novel two-stage convolutional neural network model. Medical Physics, 2021, 48.
Pan Jiawei, Wu Guoqing, Yu Jinhua, et al. Detecting the Early Infarct Core on Non-Contrast CT Images with a Deep Learning Residual Network. Journal of Stroke and Cerebrovascular Diseases, 2021, 30(6):105752.
Wu Guoqing, Shi Zhifeng, Chen Yinsheng, et al. A Sparse Representation-based Radiomics for Outcome Prediction of Higher Grade Gliomas. Medical Physics, 2018, 46.
Wu Guoqing#, Lin Jixian#, Wang Yuanyuan*, et al. Early identification of ischemic stroke in noncontrast computed tomography. Biomedical Signal Processing and Control, 2019, 52(JUL.):41-52.
Wu Guoqing, Chen Yinsheng, Wang Yuanyuan*, et al. Sparse representation-based radiomics for the diagnosis of brain tumors. IEEE Transactions on Medical Imaging, 2017.
吴国庆, 李泽榉, 汪源源,等. 基于稀疏表示体系的原发性脑部淋巴瘤和胶质母细胞瘤图像鉴别. 生物医学工程学杂志, 2018, 35(5):7.
GuoqingWu, YuanyuanWang, JinhuaYu. 3D Texture Feature Learning for Noninvasive Estimation of Gliomas Pathological Subtype/ International MICCAI Brainlesion Workshop. Springer, Cham, 2018.
Wu Guoqing, Wang Yuanyuan*, Yu Jinhua*. Overall Survival Time Prediction for High Grade Gliomas Based on Sparse Representation Framework. Springer, Cham, 2017.
Liu Shujun*, Wu Guoqing, Liu Hongqing, et al. Image restoration approach using a joint sparse representation in 3D-transform domain. Digital Signal Processing, 2017, 60:307-323.
Liu Shujun*, Wu Guoqing, Zhang Xinzheng, et al. SAR despeckling via classification-based nonlocal and local sparse representation. Neurocomputing, 2016, 219(JAN.5):174-185.
主持项目：
国家自然科学基金青年项目
教育部产学研创新基金项目
中国博士后科学基金面上项目
复旦大学人才引进项目
复旦大学医工交叉项目
获奖：
2025年 日内瓦国际发明展金奖
2025年 全国大学生生物医学工程创新设计竞赛
2023年 第二十五届中国国际高新技术成果交易会优秀产品奖
2023年 复旦大学优秀博士后
2022年 复旦大学优秀博士论文
2019年 飞利浦医疗产品创意大赛铜奖
2019年 上海市超级博士后
2018年 博士国家奖学金