基本信息

李志成 

中国科学院深圳先进技术研究院

生物医学与健康工程研究所

医学人工智能研究中心


医学成像科学与技术系统全国重点实验室


研究员,博士/博士后,博士生导师

医学人工智能研究中心副主任


国家重点研发计划项目首席科学家(重大科学仪器专项)

科技部青年科学家

中国科学院特聘研究员岗位

广东省“特支计划”青年拔尖人才

中科院青年创新促进会会员

深圳市孔雀计划海外高层次创新人才

深圳市后备级高层次人才


《European Radiology》编委

《Translational Oncology》编委

《Displays》编委


ORCID: 0000-0003-4140-0580

Home at Researchgate

Home at Publons

Scopus Profile: 55707186500

Loop Profile: 785003


电子邮件:zc.li <at> siat.ac.cn
通信地址:深圳市南山区西丽深圳大学城学苑大道1068号
邮政编码:518055

研究领域

面向脑肿瘤等复杂疾病精准诊疗的多模态多尺度人工智能新方法和新应用,包括影像-病理-基因融合分析、多模态多尺度人工智能算法、肿瘤分型分级和预后评估、以及高分辨多模态生物医学成像方法和仪器研制。研发的脑胶质瘤IDH1突变影像学智能检测方法、数字病理整合诊断系统已在临床试用。

招生信息

   
招生专业
083100-生物医学工程
081104-模式识别与智能系统
081002-信号与信息处理
招生方向
医学影像与深度学习,肿瘤影像-基因组学智能分析
X射线相衬荧光成像

工作经历

   
社会兼职与学术团体

1、医学影像综合类期刊《European Radiology》(IF=7.0) 编委,负责神经影像人工智能诊疗的稿件

2、临床肿瘤类综合期刊《Translational Oncology》(IF=4.8) 编委,负责医学影像机器学习的稿件

3、计算机视觉和图像处理类期刊《Displays》(IF=3.1)编委,负责医学影像分析和处理的稿件

4、基因组类期刊《Genes》(IF=4.1)客座编辑,负责组办主题为Advanced in Radiogenomics的Special Issue

5、Nature出版集团旗下综合性期刊《Scientific Reports》(IF=4.6)编委,负责生物医学工程领域的稿件

6、中国科学院青年创新促进会会员

7、欧洲放射学会通信会员

8、中国生物医学工程学会医学物理分会 第一届青年委员

9、中国民族卫生协会放射分会 第二届委员会常委

10、中国研究型医院协会 感染与炎症放射专委会 第二届委员

11、中国抗癌协会 肿瘤人工智能专委会专业会员 青年理事会会员

12、医学图像计算青年研讨会(MICS) 第四届委员

13、广东省医学会医学人工智能分会 首届委员

14、广东省医学会肿瘤影像与大数据专委会 首届委员

15、广东省医学会放射医学 分会会员

16、深圳市医疗器械行业 中级职称评审专家

17、IEEE会员、IEEE EMBS会员、IOMP会员

18、Nature Communications, Medical Image Analysis, TMI, EBioMedicine, European Radiology等期刊审稿人

教授课程

   
博士课程

中国科学院深圳先进技术研究院博士生学位课程


2017 医学影像中的机器学习方法

2019 医学影像中的人工智能

2020 医学影像中的人工智能

专利与奖励

奖励与人才项目

1、2019年 获评吴文俊人工智能技术发明二等奖 面向消化道内镜的人工智能图像技术及应用 中国人工智能学会

2、2017年 入选中国科学院青年创新促进会会员 中国科学院

3、2015年 获评广东省科技创新青年拔尖人才 广东省科技厅

4、2014年 获评国家863计划青年科学家  科技部

5、2008年 获评中华人民共和国驻新加坡大使馆颁发的优秀公派留学生奖 中国驻新加坡大使馆


发明专利

1、对三维目标建立统计形状模型的方法

2、组织器官三维可视化手术导航系统

3、X射线光栅相衬成像CT系统

4、一种微聚焦X光源类同轴相衬成像自动化系统

5、三维X射线成像系统

6、多模态影像组学的分析方法、装置及终端

出版信息

   
发表论文

# indicates equal contribution authors. * indicates corresponding authors.

· Yuanshen Zhao#, Weiwei Wang#, Yuchen Ji, Yang Guo, Jingxian Duan, Xianzhi Liu, Dongming Yan, Dong Liang, Wencai Li, Zhenyu Zhang*, Zhi-Cheng Li*. Computational pathology for prediction of Isocitrate Dehydrogenase gene mutation from whole-slide images in adult patients with diffuse glioma. The American Journal of Pathology. 194(5): 747-758. 2024. IF:6.0. https://doi.org/10.1016/j.ajpath.2024.01.009

· Zijia Liu*, Jin Han*, Jiannan Liu*, Zhi-Cheng Li*, Guangtao Zhai*. Neighborhood evaluator for efficient super-resolution reconstruction of 2D medical images. Computers in Biology and Medicine. 171: 108212. 2024. IF:7.7. https://doi.org/10.1016/j.compbiomed.2024.108212

· Weiwei Wang#, Yuanshen Zhao#, Lianghong Teng#,Jing Yan#, Yang Guo, Yuning Qiu, Yuchen Ji, Bin Yu, Dongling Pei, Wenchao Duan, Minkai Wang, Li Wang, Jingxian Duan, Qiuchang Sun, Shengnan Wang, Huanli Duan, Chen Sun, Yu Guo, Lin Luo, Zhixuan Guo, Fangzhan Guan, Zilong Wang, Aoqi Xing, Zhongyi Liu, Hongyan Zhang, Li Cui, Lan Zhang, Guozhong Jiang, Dongming Yan, Xianzhi Liu, Hairong Zheng, Dong Liang, Wencai Li*, Zhi-Cheng Li*, Zhenyu Zhang*. Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images. Nature Communications. 14: 6359. 2023. IF:16.6. https://doi.org/10.1038/s41467-023-41195-9

· Jingxian Duan#, Yuanshen Zhao#, Qiuchang Sun, Dong Liang, Zaiyi Liu, Xin Chen*, Zhi-Cheng Li*. Imaging‐proteomic analysis for prediction of neoadjuvant chemotherapy responses in patients with breast cancer. Cancer Medicine. 12(23): 21256-21269, 21256-21269. 2023. IF:4.0. https://doi.org/10.1002/cam4.6704

· Tao Huang, Huiyu Xu, Haitao Wang, Haofan Huang, Yongjun Xu, Baohua Li, Shenda Hong, Guoshuang Feng, Shuyi Kui, Guangjian Liu, Dehua Jiang, Zhi-Cheng Li, Ye Li, Congcong Ma, Chunyan Su, Wei Wang, Rong Li, Puxiang Lai*, Jie Qiao*. Artificial intelligence for medicine: Progress, challenges, and perspectives. The Innovation Medicine. 1(2): 100030. 2023. https://doi.org/10.59717/j.xinn-med.2023.100030

· Haifeng Wang, Zhanqi Hu, Dian Jiang, Rongbo Lin, Cailei Zhao, Xia Zhao, Yihang Zhou, Yanjie Zhu, Hongwu Zeng, Dong Liang, Jianxiang Liao*, Zhicheng Li. Predicting antiseizure medication treatment in children with rare tuberous sclerosis complex–related epilepsy using deep learning. American Journal of Neuroradiology. 44 (12): 1373-1383. 2023. IF:3.5. https://doi.org/10.3174/ajnr.A8053

· Dian Jiang#, Jianxiang Liao#, Cailei Zhao, Xia Zhao, Rongbo Lin, Jun Yang, Zhi-Cheng Li, Yihang Zhou, Yanjie Zhu, Dong Liang, Zhanqi Hu*, Haifeng Wang*. Recognizing pediatric tuberous sclerosis complex based on multi-contrast MRI and deep weighted fusion network. Bioengineering. 10(7): 870. https://doi.org/10.3390/bioengineering10070870

· Jingxian Duan, Yuanshen Zhao, Zeyu Zhang,  Dong Liang, Zhi-Cheng Li*, Zaiyi Liu, Xin Chen. Imaging-proteomics co-profiling reveals biologic pathways underlying prognostic MRI features. In Proc. of 15th Biomedical Engineering International Conference (BMEiCON 2023). Tokyo, Japan, 2023. https://doi.org/10.1109/BMEiCON60347.2023.10321994

· Yuanshen Zhao#, Longsong Li#, Ke Han, Tao Li, Jingxian Duan, Qiuchang Sun, Chaofan Zhu, Dong Liang, Ningli Chai*, Zhi-Cheng Li*.  A radio-pathologic integrated model for prediction of lymph node metastasis stage in patients with gastric cancer. Abdominal Radiology. 48: 3332–3342. 2023. https://doi.org/10.1007/s00261-023-04037-2

· Dongling Pei#, Xuanke Hong#, Linglong Wang#, Fangzhan Guan, Weiwei Wang, Yuning Qiu, Xueping Zhang, Wenchao Duan, Minkai Wang, Chen Sun, Yuanshen Zhao, Jingxian Duan, Qiuchang Sun, Yuchen Ji, Dongming Yan, Xianzhi Liu, Jingliang Cheng, Zhenyu Zhang, Zhi-Cheng Li*, Jing Yan*. Radiomics Features from Multiparametric Magnetic Resonance Imaging Predict Molecular Subgroups of Pediatric Low-grade Gliomas. BMC Cancer. 23: 848. 2023. IF:3.8. https://doi.org/10.1186/s12885-023-11338-8

· Wenxia Wu, Jing Yan, Dong Liang, Zhenyu Zhang, Zhi-Cheng Li*. Semi-supervised Medical Image Segmentation with Multiscale Contrastive Learning and Cross-Supervision. In Proc. of 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023). Sydney, Australia. July 2023. https://doi.org/10.1109/EMBC40787.2023.10341018

· Wenxia Wu#, Jing Yan#, Yuanshen Zhao, Qiuchang Sun, Huailing Zhang, Jingliang Cheng, Dong Liang, Yinsheng Chen, Zhenyu Zhang*, Zhi-Cheng Li*. Multi-task learning for concurrent survival prediction and semi-supervised segmentation of gliomas in brain MRI. Displays. 78:102402. 2023. IF:3.1.  https://doi.org/10.1016/j.displa.2023.102402 

· Jingxian Duan#, Zhenyu Zhang#, Yinsheng Chen#, Yuanshen Zhao, Qiuchang Sun, Weiwei Wang, Hairong Zheng, Dong Liang, Jingliang Cheng*, Jing Yan*, and Zhi-Cheng Li*. Imaging phenotypes from MRI for the prediction of glioma immune subtypes from RNA sequencing: a multicenter study. Molecular Oncology. 17(4): 629-646, 2023. IF: 7.45. https://doi.org/10.1002/1878-0261.13380

· Jing Yan#, Qiuchang Sun#, Xiangliang Tan#, Chaofeng Liang, Hongmin Bai, Wenchao Duan, Tianhao Mu, Yang Guo, Yuning Qiu, Weiwei Wang, Qiaoli Yao, Dongling Pei, Yuanshen Zhao, Danni Liu, Jingxian Duan, Shifu Chen, Chen Sun, Wenqing Wang, Zhen Liu, Xuanke Hong, Xiangxiang Wang, Yu Guo, Yikai Xu, Xianzhi Liu, Jingliang Cheng*, Zhi-Cheng Li*, and Zhenyu Zhang*. Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center study. European Radiology. 33: 904–914, 2023. IF: 7.02. https://doi.org/10.1007/s00330-022-09066-x

· Huixia You, Yuanshen Zhao, Qiuchang Sun, Wenxia Wu, Xiaofei Lv, Yinsheng Chen, Huailing Zhang, Zhi-Cheng Li*. Deep learning MRI signature to predict survival and treatment benefit from temozolomide in IDH-wildtype glioblastoma. Displays. 2023. IF: 3.1. https://doi.org/10.1016/j.displa.2023.102399

· Haiyan Wang, Yaping Wu, Zhenxing Huang, Zhi-Cheng Li, Na Zhang, Fangfang Fu, Nan Meng, Haining Wang, Yun Zhou, Yongfeng Yang, Xin Liu, Dong Liang, Hairong Zheng, Greta S. P. Mok, Meiyun Wang*, and Zhanli Hu*. Deep learning–based dynamic PET parametric Ki image generation from lung static PET. European Radiology. 2022. IF: 7.02. https://doi.org/10.1007/s00330-022-09237-w

· Yuanshen Zhao, Jingxian Duan, Zhi-Cheng Li, Ningli Chai, Longsong Li. A radiopathomics model for prognosis prediction in patients with gastric cancer. In Proc. of 14th Biomedical Engineering International Conference (BMEiCON 2022). Songkhla, Thailand, 2022. https://doi.org/10.1109/BMEiCON56653.2022.10012107

· Zhi-Cheng Li#, Jing Yan#, Shenghai Zhang#, Chaofeng Liang, Xiaofei Lv, Yan Zou, Huailing Zhang, Dong Liang, Zhenyu Zhang*, Yinsheng Chen*. Glioma survival prediction from whole-brain MRI without tumor segmentation using deep attention network: A multicenter study. European Radiology. 32: 5719–5729, 2022. IF:7.02. https://doi.org/10.1007/s00330-022-08640-7

· Yizhou Chen, Xu-Hua Yang, Zihan Wei, Ali Asghar Herdari, Nenggan Zheng, Zhi-Cheng Li, Huiling Chen*, Haigen Hu, Qianwei Zhou, Qiu Guan*. Generative adversarial networks in medical image augmentation: a review. Computers in Biology and Medicine. 144(1): 105382. 2022. ESI高被引论文 IF:6.70. https://doi.org/10.1016/j.compbiomed.2022.105382

· Jing Yan#, Shenghai Zhang#, Qiuchang Sun, Weiwei Wang, Wenchao Duan, Li Wang, Tianqing Ding, Dongling Pei, Chen Sun, Wenqing Wang, Zhen Liu, Xuanke Hong, Xiangxiang Wang, Yu Guo, Wencai Li, Jingliang Cheng, Xianzhi Liu, Zhi-Cheng Li*, Zhenyu Zhang*. Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study. Laboratory Investigation. 102, 154–159, 2022. IF:5.5. https://doi.org/10.1038/s41374-021-00692-5 

· Jianeng Liu, Yinsheng Chen, Jing Yan, Zhenyu Zhang, Huailing Zhang, Zhi-Cheng Li#. Risk Attention Network: Weakly-Supervised Learning for Joint Tumor Segmentation and Survival Prediction. IFTC 2021. Communications in Computer and Information Science, vol 1560. Springer, Singapore.  https://doi.org/10.1007/978-981-19-2266-4_8

· Qiuchang Sun#, Yinsheng Chen#, Chaofeng Liang, Yuanshen Zhao, Xiaofei Lv, Yan Zou, Kai Yan, Hairong Zheng, Dong Liang, Zhi-Cheng Li*. Biologic pathways underlying prognostic radiomics phenotypes from paired MRI and RNA sequencing in glioblastoma. Radiology. 301(3): 654-663, 2021. IF:29.1. https://doi.org/10.1148/radiol.2021203281

· Jing Yan#, Yuanshen Zhao#, Yinsheng Chen#, Weiwei Wang, Wenchao Duan, Li Wang, Shenhai Zhang, Tianqing Ding, Lei Liu, Qiuchang Sun, Dongling Pei, Yunbo Zhan, Haibiao Zhao, Tao Sun, Chen Sun, Wenqing Wang, Zhen Li, Xuanke Hong, Xiangxiang Wang, Yu Guo, Wencai Li, Jingliang Cheng, Xianzhi Liu, Xiaofei Lv*, Zhi-Cheng Li*, Zhenyu Zhang*. Deep learning features from diffusion tensor imaging improve glioma stratification and identify risk groups with distinct molecular pathway activities. EBioMedicine. 72: 103583, 2021. IF:11.2. https://doi.org/10.1016/j.ebiom.2021.103583

· Shu Zhou, Qingchun Meng, Lingyu Li, Luo Hai, Zexuan Wang, Zhicheng Li*, Yingli Sun*. Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies. Frontiers in Genetics. 12: 758103, 2021. IF:4.8. https://doi.org/10.3389/fgene.2021.758103

· Hongyu Chen#, Fuhua Lin#, Jinming Zhang, XIaofei Lv, Jian Zhou, Zhi-Cheng Li*, Yinsheng Chen*. Deep learning radiomics to predict PTEN mutation status from magnetic resonance imaging in patients with glioma. Frontiers in Oncology. 11: 734433, 2021. IF:5.7. https://doi.org/10.3389/fonc.2021.734433

· Nian Lu#, Weijing Zhang#, Lu Dong#, Junying Chen, Yanlin Zhu, Shenghai Zhang, Jianhua Fu, Shaohan Yin, Zhi-Cheng Li*, Chuanmiao Xie. Dual-region radiomics signature: Integrating primary tumor and lymph node computed tomography features improves survival prediction in esophageal squamous cell cancer. Computer Methods and Programs in Biomedicine. 208(2): 106287, 2021. IF:7.0. https://doi.org/10.1016/j.cmpb.2021.106287

· Ronghui Luo#, Yongshuai Ge#, Zhanli Hu#, Dong Liang*, Zhi-Cheng Li*. DeepPhase: Learning phase contrast signal from dual energy X-ray absorption images. Displays. 69(4): 102027, 2021. IF:3.1. https://doi.org/10.1016/j.displa.2021.102027

· Yuanshen Zhao#, Guiqin Liu#, Qiuchang Sun, Guangtao Zhai, Guangyu Wu*, Zhi-Cheng Li*. Validation of CT radiomics for prediction of distant metastasis after surgical resection in patients with clear cell renal cell carcinoma: exploring the underlying signaling pathways. European Radiology. 31: 5032-5040, 2021. IF:7.0. https://doi.org/10.1007/s00330-020-07590-2

· Tianding Ding, Zhengyu Zhang, Jing Yan, Qiuchang Sun, Yuanshen Zhao, Zhi-Cheng Li*. GaLNet: Weakly-Supervised Learning for Evidence-Based Tumor Grading and Localization in MR Imaging. In Proceeding of Digital TV and Wireless Multimedia Communication. IFTC 2020. Communications in Computer and Information Science, vol 1390. Springer, Singapore. https://doi.org/10.1007/978-981-16-1194-0_22

· JingYan#, Shenghai Zhang#, Kay Ka-Wai Li#, Weiwei Wang, Ke Li, Wenchao Duan, Binke Yuan, Li Wang, Lei Liu, Yunbo Zhan, Dongling Pei, Haibiao Zhao, Tao Sun, Chen Sun, Wenqing Wang, Zhen Liu, Xuanke Hong, Xiangxiang Wang, Yu Guo, Wencai Li, Jingliang Cheng, Xianzhi Liu, Ho-Keung Ng, Zhicheng Li*, Zhenyu Zhang*.  Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma. EBioMedicine. 61: 103093, 2020. IF:11.2. https://doi.org/10.1016/j.ebiom.2020.103093

· Jing Yan#, Lei Liu#, Weiwei Wang#, Yuanshen Zhao#, Kai-Wai Kay, Ke Li, Li Wang, Binke Yuan, Haiyang Geng, Shenghai Zhang, Zhen Liu, Wenchao Duan, Yunbo Zhan, Dongling Pei, Haibiao Zhao, Tao Sun, Chen Sun, Wenqing Wang, Xuanke Hong, Yu Guo, Wencai Li, Jingliang Cheng, Xianzhi Liu, Ho-Keung Ng, Zhi-Cheng Li*, Zhenyu Zhang*. Radiomic features from multi-parameter MRI combined with clinical parameters predict molecular subgroups in patients with medulloblastoma. Frontiers in Oncology. 10: 558162, 2020. IF:5.7. https://doi.org/10.3389/fonc.2020.558162

· Shifu Chen*, Changshou He, Yingqiang Li, Zhicheng Li, Charles E Melancon III. A computational toolset for identification of SARS-CoV-2, other viruses and microorganisms from sequencing data. Briefings in Bioinformatics. 22(2): 924-935, 2020. IF:14.0. https://doi.org/10.1093/bib/bbaa231

· Shenghai Zhang#, Mengfan Song#, Yuanshen Zhao, Shuaishuai Xu, Qiuchang Sun, Guangtai Zhai, Dong Liang, Guangyu Wu*, Zhi-Cheng Li*. Radiomics Nomogram for Preoperative Prediction of Recurrence-Free Survival Using Diffusion-Weighted Imaging in Patients with Muscle-Invasive Bladder Cancer. European Journal of Radiology. 131: 109219, 2020. IF:4.5. https://doi.org/10.1016/j.ejrad.2020.109219

· Zhanli Hu, Zixiang Chen, Chao Zhou, Xuda Hong, Jianwei Chen, Qiyang Zhang, Changhui Jiang, Yongshuai Ge, Yongfeng Yang, Xin Liu, Hairong Zheng, Zhi-Cheng Li*, Dong Liang*. Evaluation of reconstruction algorithms for a stationary digital breast tomosynthesis system using a carbon nanotube X-ray source array. Journal of X-Ray Science and Technology. 28(6): 1157-1169, 2020. IF:2.4. https://doi.org/10.3233/XST-200668

· Yongshuai Ge#, Peizhen Liu#, Yifan Ni#, Jianwei Chen, Jiecheng Yang, Ting Su, Huitao Zhang, Jinchuan Guo, Hairong Zheng, Zhi-Cheng Li*, Dong Liang*. Enhancing the X-ray differential phase contrast image quality with deep learning technique. IEEE Transactions on Biomedical Engineering. 68(6): 1751-1758, 2020. IF:4.8. https://doi.org/10.1109/TBME.2020.3011119 

· Qiuchang Sun#, Xiaona Lin#, Yuanshen Zhao, Ling Li, Kai Yan, Dong Liang, Desheng Sun*, Zhi-Cheng Li*. Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region. Frontiers in Oncology. 10:53, 2020. ESI高被引论文 IF:5.7. https://doi.org/10.3389/fonc.2020.00053

· Shuaishuai Xu, Qiuying Yao, Guiqin Liu, Di Jin, Haige Chen, Jianrong Xu, Zhicheng Li*, Guangyu Wu*. Combining DWI radiomics features with transurethral resection promotes the differentiation between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer. European Radiology. 30:1804–1812. 2020. IF:7.0. https://doi.org/10.1007/s00330-019-06484-2

· Kai Yan, Qiuchang Sun, Ling Li, Zhi-Cheng Li*. 3D Deep Residual Encoder-Decoder CNNS with Squeeze-and-Excitation for Brain Tumor Segmentation. In Proc of The International MICCAI Brainlesion Workshop. Brats Challenge. BrainLes 2019: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. https://doi.org/10.1007/978-3-030-46643-5_23

· Shifu Chen, Yanqing Zhou, Yaru Chen, Tanxiao Huang, Wenting Liao, Yun Xu, Zhicheng Li, Jia Gu. Gencore: an efficient tool to generate consensus reads for error suppressing and duplicate removing of NGS data. BMC Bioinformatics. 20:606. 2019. IF:3.3. https://doi.org/10.1186/s12859-019-3280-9 

· Jingxian Duan, Yuling Wu, Jikui Liu, Jiajia Zhang, Zhichao Fu, Tieshan Feng, Ming Liu, Jia Han, Zhicheng Li, Shifu Chen. Genetic biomarkers for hepatocellular carcinoma in the era of precision medicine. Journal of Hepatocellular Carcinoma. 6: 151-166, 2019. IF:5.0. https://doi.org/10.2147/JHC.S224849

· Jianwen Chen#, Jiongtao Zhu#, Zhi-Cheng Li#, Wei Shi, Qiyang Zhang, Zhanli Hu, Hairong Zheng, Dong Liang*, Yongshuai Ge*. Automatic image-domain Moiré artifact reduction method in grating-based x-ray interferometry imaging. Physics in Medicine and Biology. 64(19): 195013. 2019. IF:4.2. https://doi.org/10.1088/1361-6560/ab3c34

· Zijia Liu, Qiuchang Sun, Hongmin Bai, Chaofeng Liang, Yinsheng Chen, Zhi-Cheng Li. 3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma. In Proc of The 26th IEEE International Conference on Image Processing (ICIP 2019). Taipei. September 22-25, 2019. https://doi.org/10.1109/ICIP.2019.8803077

· Zhi-Cheng Li, Guang-yu Wu, Jinheng Zhang, Zhongqiu Wang, Guiqin Liu, Dong Liang. Towards an Interpretable Radiomics Model for Classifying Renal Cell Carcinomas Subtypes: A Radiogenomics Assessment. In Proc of IEEE International Symposium on Biomedical Imaging (ISBI). Venice, Italy. April 8-11, 2019. https://doi.org/10.1109/ISBI.2019.8759592

· Zhi-Cheng Li#, Guangtao Zhai#, Jinheng Zhang, Zhongqiu Wang, Guiqin Liu*, Guang-yu Wu*, Dong Liang, Hairong Zheng. Differentiation of Clear Cell and Non-Clear Cell Renal Cell Carcinomas by All-Relevant Radiomics Features from Multiphase CT: A VHL mutation Perspective. European Radiology. 29: 3996-4007. 2018. IF:7.0.  https://doi.org/10.1007/s00330-018-5872-6

· Zhi-Cheng Li#, Hongmin Bai#, Qiuchang Sun, Yuanshen Zhao, Yanchun Lv, Jian Zhou, Yinsheng Chen*, Chaofeng Liang*, Dong Liang, Hairong Zheng. Multiregional Radiomics Profiling from Multiparametric MRI: Identifying an Imaging Predictor of IDH1 Mutation Status in Glioblastoma. Cancer Medicine. 7(12): 5999-6009. 2018. IF:4.7. https://doi.org/10.1002/cam4.1863

· Ting Xiao#, Lei Liu#, Kai Li#, Wenjian Qin, Shaode Yu, Zhi-Cheng Li*. Comparison of transferred deep neural networks in ultrasonic breat masses discrimination. BioMed Research International. 2018: 4605191, 2018. IF:3.2. https://doi.org/10.1155/2018/4605191

· Zhi-Cheng Li, Yinsheng Chen, Qiuchang Sun, Qihua Li, Lei Liu, Ronghui Luo, Hongmin Bai, Chaofeng Liang. Multiregional radiomics phenotypes at MR imaging predict MGMT promoter methylation in Glioblastoma. In Proc of World Congress on Medical Physics & Biomedical Engineering. Prague, Czech. June 3-8, 2018.  (Oral Presentation) https://doi.org/10.1007/978-981-10-9035-6_25

· Zhi-Cheng Li#, Hongmin Bai#, Qiuchang Sun, Qihua Li, Lei Liu, Yan Zou, Yinsheng Cheng*, Chaofeng Liang*, Hairong Zheng. Multiregional Radiomics Features from Multiparametric MRI for Prediction of MGMT Methylation Status in Glioblastoma Multiforme: A Multicenter Study. European Radiology. 28(9):3640–3650, 2018. IF:7.0. https://doi.org/10.1007/s00330-017-5302-1

· Qihua Li#, Hongmin Bai#, Yinsheng Chen, Qiuchang Sun, Lei Liu, Sijie Zhou, Guoliang Wang, Chaofeng Liang*, Zhi-Cheng Li*. A Fully-Automatic Multiparametric Radiomics Model: Towards Reproducible and Prognostic Imaging Signature for Prediction of Overall Survival in Glioblastoma Multiforme. Scientific Reports, 7:14331, 2017. IF:5.0. https://doi.org/10.1038/s41598-017-14753-7

· Jiangwei Lao#, Yinsheng Chen#, Zhi-Cheng Li*, Qihua Li, Ji Zhang, Jing Liu, Guangtao Zhai*. A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme. Scientific Reports, 7:10353, 2017. IF:5.0. https://doi.org/10.1038/s41598-017-10649-8 (rank 5 in TOP 100 scientific reports oncology papers in 2017, ESI高被引论文)

· Zhi-Cheng Li, Qihua Li, Qiuchang Sun, Ronghui Luo, Yinsheng Chen. Identifying A Radiomics Imaging Signature for Prediction of Overall Survival in Glioblastoma Multiforme. The 2017 Biomedical Engineering International Conference (BMEiCON-2017), Sapporo, Japan. Sept. 2017. https://doi.org/10.1109/BMEiCON.2017.8229098

· Zhi-Cheng Li, Yinsheng Chen, Qihua Li, Qiuchang Sun, Ronghui Luo. Automatic Extraction of MRI Radiomics Features in Glioblastoma Multiforme: A Reproducibility Evaluation. IEEE International Conference on Cybernetics (CYBCONF-2017), Exeter, UK. Jun 2017. https://doi.org/10.1109/CYBConf.2017.7985762

· Xiaokun Liang, Zhicheng Zhang, Tianye Niu, Shaode Yu, Shibin Wu, Zhicheng Li, Huailing Zhang, Yaoqin Xie. Iterative Image-Domain Ring Artifact Removal in Cone-Beam CT. Physics in Medicine and Biology, 62(13), 2017. IF:4.2. https://doi.org/10.1088/1361-6560/aa7017

· Zhi-Cheng Li, Qihua Li, Bolin Song, Yinsheng Chen, Qiuchang Sun, Yaoqin Xie, Lei Wang. Clustering of MRI Radiomics Features for Glioblastoma Multiforme: An Initial Study. in Proc. 7th International Conference on Biomedical Imaging and Augmented Reality (MIAR 2016), Bern, Switzerland, Aug. 2016. https://doi.org/10.1007/978-3-319-43775-0_28

· Zhi-Cheng Li, Kai Li, Ken Chen, Yaoqin Xie. Accurate Kidney Surface Reconstruction from 3D Ultrasonography for Volume Assessment: First Clinical Evaluation. in Proc. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015), Milan, Italy. Aug. 2015. https://doi.org/10.1109/EMBC.2015.7319018

· Zhi-Cheng Li, Geng Niu, Kai Li, Hai-Lun Zhan, Yao-Qin Xie, Lei Wang. Augmented Reality Using 3D Shape Model for  Ultrasound-Guided Percutaneous Renal Access: A Pig Model Study. in Proc. The 2014 7th Biomedical Engineering International Conference (BMEiCON-2014), Fukuoka, Japan. Nov. 2014. (Oral Presentation) https://doi.org/10.1109/BMEiCON.2014.7017362

· Zhi-Cheng Li, Kai Li, Hailun Zhan, Ken Chen, Minming Chen, Yaoqin Xie, Lei Wang. Augmenting Interventional Ultrasound Using Statistical Shape Model for Guiding Percutaneous Nephrolithotomy: Initial Evaluation in Pigs. Neurocomputing, 144:58-69, 2014. IF:5.8. https://doi.org/10.1016/j.neucom.2014.01.059

· Hailun Zhan#, Zhi-Cheng Li#, Xiangfu Zhou, Fei Yang, Jiefu Huang, Minhua Lu. Supine-lithotomy versus prone position in minimally invasive percutaneous nephrolithotomy for upper urinary tract calculi. Urologia Internationalis, 91:320-325, 2013. IF:1.9. https://doi.org/10.1159/000351337

· Dongwen Zhang#, Zhi-Cheng Li#, Ken Chen, Jing Xiong, Xuping Zhang, Lei Wang. An optical tracker based robot registration and servoing method for ultrasound guided percutaneous renal access. Biomedical Engineering Online. 12:47, 2013. IF:3.9. https://doi.org/10.1186/1475-925X-12-47

· Gaoyuan Dai, Zhi-Cheng Li, Jia Gu, Lei Wang, Xingmin Li. Segmentation of Kidneys from Computed Tomography Using 3D Fast GrowCut Algorithm. in Proc. IEEE International Conference on Image Processing (ICIP), Melbourne, Australia. Sep. 2013. https://doi.org/10.1109/ICIP.2013.6738236

· Honglin Wan#, Zhi-Cheng Li#, Jianping Qiao, Baosheng Li. Non-ideal Iris Segmentation Using Anisotropic Diffusion. IET Image Processing. 7(2): 111-120. 2013. IF:1.8. https://doi.org/10.1049/iet-ipr.2012.0084

· Zhi-Cheng Li, Kai Li, Hailun Zhan, Ken Chen, Jia Gu and Lei Wang. Augmenting Intraoperative Ultrasound with Preoperative Magnetic Resonance Planning Models for Percutaneous Renal Access. Biomedical Engineering Online. 11:60, 2012. IF:3.9. https://doi.org/10.1186/1475-925X-11-60

· Guoyan Zheng, Zhi-Cheng Li and Jia Gu. Evaluation of 3D Correspondence Methods for Building Point Distribution Models of the Kidney. in Proc. the 5th International Conference on BioMedical Engineering and Informatics (BMEI 2012), Chengdu, China. Oct. 2012. https://doi.org/10.1109/BMEI.2012.6512977

· Zhi-Cheng Li, Kai Li, Ken Chen and et al. Comparison of 2D and 3D Ultrasound Guided Percutaneous Renal Puncture. in Proc. World Congress on Medical Physics and Biomedical Engineering, Beijing, China. May 2012. (Oral Presentation) https://doi.org/10.1007/978-3-642-29305-4_185

· Ken Chen, Zhi-Cheng Li and Jia Gu. Registration of Magnetic Resonance and 3D Ultrasound for Renal Intervention. in Proc. International Conference on Computer Science and Electronics Engineering (ICCSEE), Mar. 2012. https://doi.org/10.1109/ICCSEE.2012.303

· Ken Chen, Zhi-Cheng Li, Ling Li and Jia Gu. Three dimensional Ultrasound Guided Percutaneous Renal Puncture: A Phantom Study. in Proc. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), HongKong. Jan. 2012. (Oral Presentation) https://doi.org/10.1109/BHI.2012.6211675

· Zhi-Cheng Li, Jia Gu, Jacob Chakareski , Lei Wang. Ultrasound-based Surgical Navigation for Percutaneous Renal Intervention: In vivo Measurements and In vitro Assessment. in Proc. IEEE International Conference on Image Processing (ICIP), Brussel, Belgium. Sep. 2011. https://doi.org/10.1109/ICIP.2011.6116067

· Zhi-Cheng Li, Jacob Chakareski, Lili Shen and Lei Wang. Video Quality in Transmission over Burst-Loss Channels: A Forward Error Correction Perspective. IEEE Communications Letters, 15(2): 238-240. 2011. IF:3.6. https://doi.org/10.1109/LCOMM.2011.122810.101931

· Zhi-Cheng Li, Jacob Chakareski, Xiaodun Niu, Yongjun Zhang and Wanyi Gu. Modeling and Analysis of Distortion Caused by Markov-Model Burst Packet Losses in Video Transmission. IEEE Transactions on Circuits and Systems for Video Technology, 19(7): 917-931, 2009. IF:5.9. https://doi.org/10.1109/TCSVT.2009.2022806





科研活动

   
科研项目

·  高时空分辨率光学和能谱显微CT双模态成像仪,主持项目负责人,科技部重点研发计划项目-重大科学仪器专项,总经费3600万,其中国拨1200万,2023.12.01-2026.11.30

·  基于多组学数据深度学习的肠-脑轴肿瘤免疫调控网络研究,课题组段静娴主持,深圳市医学研究专项-青年项目,80万,2024.01.01-2026.12.31

·  基于图深度学习的脑胶质瘤多尺度医学图像融合分析与智能建模,课题组赵源深主持,广东省自然科学基金-青年提升项目,30万,2024.01.01-2025.12.31

·  脑胶质瘤纵向融媒体智能识别与个性化辅助诊疗研究,主持,国家自然科学基金联合重点项目,260万,2021.01.01-2024.12.30

·  基于多组学深度聚类的脑胶质瘤免疫微环境亚型划分方法研究,课题组段静娴主持,国自然青年基金,30万,2023.01.01-2025.12.31

·  基于深度学习多组学的乳腺癌辅助诊疗与预后预测系统(广东省人民医院主持),参与,广东省重点领域研发计划-新一代人工智能重大专项,1000万,2021.01.01-2023.12.31

·  基于动态能谱X射线平板探测器的术中能谱CT关键技术研发,参与,深圳市技术攻关重点项目,800万,2022.01.01-2024.12.31

·  医生诊疗快速辅助支持系统,课题组参与,国自然数学天元基金-数学与医疗健康交叉重点专项,200万,2022.01.01-2025.12.31

·  基于多维扩散磁共振影像基因组学的脑胶质瘤智能亚型预测和预后评估(广东省医科大主持),参与,广东省联合重点粤莞联合项目,100万,2022.10.01-2023.09.30

·  基于生物语义的肾透明细胞癌转移预测影像组学分析方法研究,课题组赵源深主持,国自然青年基金,24.5万元,2020.01.01-2022.12.31

·  早期肿瘤的高分辨X射线相衬荧光多模CT成像研究,主持,深圳市基础研究学科布局项目,300万,2017.07.01-2019.06.30

·  中科院青年创新促进会会员,主持,80万,2018.01.01-2021.12.31

·  基于多模态影像学的缺血性脑血管病疗效预测模型研究(解放军总医院主持),参与,国自然重点基金,300万,2018.01.01-2011.12.31

·  基于多基因分子病理与多模态磁共振影像组学对比分析的胶质母细胞瘤精准预后评估模型研究(中山大学肿瘤防治中心主持),参与,广州市重点研发项目,100万,2018.01.01-2021.12.31

·  脑胶质瘤精准诊疗技术的关键科学问题研究,参与,国家973项目,2015.01.01-2019.12.31

·  脑胶质瘤空间-时间异质性的多模态磁共振自动定量分析方法及其影像基因组学应用,主持,国自然面上项目,68万,2016.01.01-2019.12.31

·  动态三维血管路图引导的脑动脉瘤介入栓塞治疗关键技术研究,主持,国家863计划青年科学家专题,120万,2015.01.01-2017.12.31

·  广东省特支计划科技创新青年拔尖人才项目,主持,30万,2015.04.01-2018.03.31

·  动态全景式3D内镜引导的软组织微创治疗关键技术研究,主持,深圳市孔雀计划技术创新项目,50万,2015.01.01-2016.12.31

·  针对珠三角地区多发性肾结石的三维超声引导经皮肾穿刺精准取石关键技术研究,主持,深圳市战略新兴产业专项,30万,2015.01.01-2016.12.31

·  高精度医学信息立体空间透视融合装置(清华大学主持),参与,国自然仪器研制项目,700万,2015.01.01-2019.12.31


合作情况

   
项目协作单位

北京天坛医院、解放军总医院、郑大一附院、中山大学肿瘤防治中心等国内多家三甲医院