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ORCIDFeng Shi 0001
Person information
- affiliation: Shanghai United Imaging Intelligence Co, Department of Research and Development, China
- affiliation: Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
- affiliation (2008 - 2016): University of North Carolina at Chapel Hill, Department of Radiology and BRIC, NC, USA
- affiliation (PhD 2008): Chinese Academy of Sciences, Institute of Automation, Beijing, China
Other persons with the same name
- Feng Shi — disambiguation page
- Feng Shi 0002
![[0000-0001-7924-6588]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7924-6588")
— Beihang University, State Key Lab of Virtual Reality Technology and Systems, Beijing, China - Feng Shi 0003 — Central South University, School of Information Science and Engineering, Changsha, China
- Feng Shi 0004 — Central South University, School of Traffic and Transportation Engineering, Changsha, China
- Feng Shi 0005 (aka: F. Bill Shi) — University of North Carolina, Odum Institute for Research in Social Science, Chapel Hill, NC, USA
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2020 – today
- 2024
[j53]Yuhang Sun, Yuning Gu, Feng Shi, Jiameng Liu, Guoqiang Li, Qianjin Feng, Dinggang Shen:
Coarse-to-fine registration and time-intensity curves constraint for liver DCE-MRI synthesis. Comput. Medical Imaging Graph. 111: 102319 (2024)- 2023
- [j52]Jinrong Yang, Xiang Li, Jie-Zhi Cheng, Zhong Xue, Feng Shi, Yuqing Ji, Xuechun Wang, Fan Yang:
Segment aorta and localize landmarks simultaneously on noncontrast CT using a multitask learning framework for patients without severe vascular disease. Comput. Biol. Medicine 160: 107002 (2023) - [j51]Xingyu Gao, Feng Shi, Dinggang Shen, Manhua Liu:
Multimodal transformer network for incomplete image generation and diagnosis of Alzheimer's disease. Comput. Medical Imaging Graph. 110: 102303 (2023) - [j50]Qingqing Yan, Fuyan Li, Yi Cui, Yong Wang, Xiao Wang, Wenjing Jia, Xinhui Liu, Yuting Li, Huan Chang, Feng Shi, Yuwei Xia, Qing Zhou, Qingshi Zeng:
Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm. J. Digit. Imaging 36(4): 1480-1488 (2023) - [j49]Qi Zhu, Yuze Zhou, Yuan Yao, Liang Sun, Feng Shi, Wei Shao, Daoqiang Zhang, Dinggang Shen:
Semi-Supervised Multi-View Fusion for Identifying CAP and COVID-19 With Unlabeled CT Images. IEEE Trans. Emerg. Top. Comput. Intell. 7(3): 887-899 (2023) - [j48]Xingyu Gao, Hongrui Liu, Feng Shi, Dinggang Shen, Manhua Liu:
Brain Status Transferring Generative Adversarial Network for Decoding Individualized Atrophy in Alzheimer's Disease. IEEE J. Biomed. Health Informatics 27(10): 4961-4970 (2023) - [j47]Chaolin Li, Mianxin Liu, Jing Xia, Lang Mei, Qing Yang, Feng Shi, Han Zhang, Dinggang Shen:
Individualized Assessment of Brain Aβ Deposition With fMRI Using Deep Learning. IEEE J. Biomed. Health Informatics 27(11): 5430-5438 (2023) - [j46]Yanbei Liu, Henan Li, Tao Luo, Changqing Zhang, Zhitao Xiao, Ying Wei, Yaozong Gao, Feng Shi, Fei Shan, Dinggang Shen:
Structural Attention Graph Neural Network for Diagnosis and Prediction of COVID-19 Severity. IEEE Trans. Medical Imaging 42(2): 557-567 (2023) - [j45]Linlin Yao, Feng Shi, Sheng Wang, Xiao Zhang, Zhong Xue, Xiaohuan Cao, Yiqiang Zhan, Lizhou Chen, Yuntian Chen, Bin Song, Qian Wang, Dinggang Shen:
TaG-Net: Topology-Aware Graph Network for Centerline-Based Vessel Labeling. IEEE Trans. Medical Imaging 42(11): 3155-3166 (2023) - [c83]Xibao Li, Xi Ouyang, Jiadong Zhang, Dongdong Gu, Zehong Cao, Zhongxiang Ding, Yiqiang Zhan, Xiang Sean Zhou, Zhong Xue, Yuyao Zhang, Feng Shi, Dinggang Shen:
MT-NeT: Multi-Modality Transfer Learning Network for Automated Carotid Vessel Wall Segmentation using Sparse Annotation in MRI. ISBI 2023: 1-4 - [c82]Xiaozhao Liu, Mianxin Liu, Lang Mei, Yuyao Zhang, Feng Shi, Han Zhang, Dinggang Shen:
Mining Fmri Dynamics with Parcellation Prior for Brain Disease Diagnosis. ISBI 2023: 1-5 - [c81]Xiaoxian Xu, Ying Wei, Jie Zheng, Zhongxiang Ding, Yiqiang Zhan, Xiang Sean Zhou, Zhong Xue, Feng Shi, Dinggang Shen:
Multi-Scale Supervised Contrastive Learning for Benign-Malignant Classification of Pulmonary Nodules in Chest Ct Scans. ISBI 2023: 1-4 - [c80]Haonan Zhang, Yuhan Zhang, Qing Wu, Jiangjie Wu, Zhiming Zhen, Feng Shi, Jianmin Yuan, Hongjiang Wei, Chen Liu, Yuyao Zhang:
Self-Supervised Arbitrary Scale Super-Resolution Framework for Anisotropic MRI. ISBI 2023: 1-5 - [c79]Xingyu Gao, Feng Shi, Dinggang Shen, Manhua Liu:
Feature-Based Transformer with Incomplete Multimodal Brain Images for Diagnosis of Neurodegenerative Diseases. PRIME@MICCAI 2023: 25-34 - [c78]Wenqi Zhou, Xiao Zhang, Dongdong Gu, Sheng Wang, Jiayu Huo, Rui Zhang, Zhihao Jiang, Feng Shi, Zhong Xue, Yiqiang Zhan, Xi Ouyang, Dinggang Shen:
HENet: Hierarchical Enhancement Network for Pulmonary Vessel Segmentation in Non-contrast CT Images. MICCAI (3) 2023: 551-560 - [c77]Feihong Liu, Yongsheng Pan, Junwei Yang, Fang Xie, Xiaowei He, Han Zhang, Feng Shi, Jun Feng, Qihao Guo, Dinggang Shen:
Identifying Alzheimer's Disease-Induced Topology Alterations in Structural Networks Using Convolutional Neural Networks. MLMI@MICCAI (2) 2023: 33-42 - [c76]Nan Zhao, Yongsheng Pan, Kaicong Sun, Yuning Gu, Mianxin Liu, Zhong Xue, Han Zhang, Qing Yang, Fei Gao, Feng Shi, Dinggang Shen:
Modeling Life-Span Brain Age from Large-Scale Dataset Based on Multi-level Information Fusion. MLMI@MICCAI (2) 2023: 84-93 - [c75]Lei Zhao, Lei Ma, Zhiming Cui, Jie Zheng, Zhong Xue, Feng Shi, Dinggang Shen:
FAST-Net: A Coarse-to-fine Pyramid Network for Face-Skull Transformation. MLMI@MICCAI (2) 2023: 104-113 - [c74]Yuhang Sun, Jiameng Liu, Feihong Liu, Kaicong Sun, Han Zhang, Feng Shi, Qianjin Feng, Dinggang Shen:
Consistent and Accurate Segmentation for Serial Infant Brain MR Images with Registration Assistance. MLMI@MICCAI (1) 2023: 186-195 - [i20]Mianxin Liu, Jingyang Zhang, Yao Wang, Yan Zhou, Fang Xie, Qihao Guo, Feng Shi, Han Zhang, Qian Wang, Dinggang Shen:
Deep learning reveals the common spectrum underlying multiple brain disorders in youth and elders from brain functional networks. CoRR abs/2302.11871 (2023) - [i19]Haonan Zhang, Yuhan Zhang, Qing Wu, Jiangjie Wu, Zhiming Zhen, Feng Shi, Jianmin Yuan, Hongjiang Wei, Chen Liu, Yuyao Zhang:
Self-supervised arbitrary scale super-resolution framework for anisotropic MRI. CoRR abs/2305.01360 (2023) - [i18]Yang Nan, Xiaodan Xing, Shiyi Wang, Zeyu Tang, Federico N. Felder, Sheng Zhang, Roberta Eufrasia Ledda, Xiaoliu Ding, Ruiqi Yu, Weiping Liu, Feng Shi, Tianyang Sun, Zehong Cao, Minghui Zhang, Yun Gu, Hanxiao Zhang, Jian Gao, Wen Tang, Pengxin Yu, Han Kang, Junqiang Chen, Xing Lu, Boyu Zhang, Michail Mamalakis, Francesco Prinzi, Gianluca Carlini, Lisa Cuneo, Abhirup Banerjee, Zhaohu Xing, Lei Zhu, Zacharia Mesbah, Dhruv Jain, Tsiry Mayet, Hongyu Yuan, Qing Lyu, Athol Wells, Simon Walsh, Guang Yang:
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge. CoRR abs/2312.13752 (2023) - 2022
- [j44]Xing-Rui Wang, Xi Ma, Liu-Xu Jin, Yan-Jun Gao, Yong-Jie Xue, Jing-Long Li, Wei-Xian Bai, Miao-fei Han, Qing Zhou, Feng Shi, Jing Wang:
Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles. Frontiers Neuroinformatics 16 (2022) - [j43]Xingyu Gao, Feng Shi, Dinggang Shen, Manhua Liu:
Task-Induced Pyramid and Attention GAN for Multimodal Brain Image Imputation and Classification in Alzheimer's Disease. IEEE J. Biomed. Health Informatics 26(1): 36-43 (2022) - [j42]Gengxin Xu, Chen Liu, Jun Liu, Zhongxiang Ding, Feng Shi, Man Guo, Wei Zhao, Xiaoming Li, Ying Wei, Yaozong Gao, Chuan-Xian Ren, Dinggang Shen:
Cross-Site Severity Assessment of COVID-19 From CT Images via Domain Adaptation. IEEE Trans. Medical Imaging 41(1): 88-102 (2022) - [j41]Feng Shi, Bojiang Chen, Qiqi Cao, Ying Wei, Qing Zhou, Rui Zhang, Yaojie Zhou, Wenjie Yang, Xiang Wang, Rongrong Fan, Fan Yang, Yanbo Chen, Weimin Li, Yaozong Gao, Dinggang Shen:
Semi-Supervised Deep Transfer Learning for Benign-Malignant Diagnosis of Pulmonary Nodules in Chest CT Images. IEEE Trans. Medical Imaging 41(4): 771-781 (2022) - [c73]Lang Mei, Mianxin Liu, Lingbin Bian, Yuyao Zhang, Feng Shi, Han Zhang, Dinggang Shen:
Modular Graph Encoding and Hierarchical Readout for Functional Brain Network Based eMCI Diagnosis. ISGIE/GRAIL@MICCAI 2022: 69-78 - [c72]Xin Tang, Jiadong Zhang, Yongsheng Pan, Yuyao Zhang, Feng Shi:
CSGAN: Synthesis-Aided Brain MRI Segmentation on 6-Month Infants. DALI@MICCAI 2022: 83-91 - [c71]Linlin Yao, Zhong Xue, Yiqiang Zhan, Lizhou Chen, Yuntian Chen, Bin Song, Qian Wang, Feng Shi, Dinggang Shen:
TaG-Net: Topology-Aware Graph Network for Vessel Labeling. ISGIE/GRAIL@MICCAI 2022: 108-117 - [c70]Linlin Yao, Zhong Xue, Yiqiang Zhan, Lizhou Chen, Yuntian Chen, Bin Song, Qian Wang, Feng Shi, Dinggang Shen:
Head and Neck Vessel Segmentation with Connective Topology Using Affinity Graph. MLMI@MICCAI 2022: 230-238 - [c69]Yuyan Ge, Zhenyu Tang, Lei Ma, Caiwen Jiang, Feng Shi, Shaoyi Du, Dinggang Shen:
Multi-scale and Focal Region Based Deep Learning Network for Fine Brain Parcellation. MLMI@MICCAI 2022: 466-475 - [i17]Mianxin Liu, Han Zhang, Feng Shi, Dinggang Shen:
Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity. CoRR abs/2209.11232 (2022) - 2021
- [j40]Dongdong Gu, Liyun Chen, Fei Shan, Liming Xia, Jun Liu, Zhanhao Mo, Fuhua Yan, Bin Song, Yaozong Gao, Xiaohuan Cao, Yanbo Chen, Ying Shao, Miaofei Han, Bin Wang, Guocai Liu, Qian Wang, Feng Shi, Dinggang Shen, Zhong Xue:
Computing infection distributions and longitudinal evolution patterns in lung CT images. BMC Medical Imaging 21(1): 57 (2021) - [j39]Qi Zhu, Haizhou Ye, Liang Sun, Zhongnian Li, Ran Wang, Feng Shi, Dinggang Shen, Daoqiang Zhang:
GACDN: generative adversarial feature completion and diagnosis network for COVID-19. BMC Medical Imaging 21(1): 154 (2021) - [j38]Junbang Feng, Yi Guo, Shike Wang, Feng Shi, Ying Wei, Yichu He, Ping Zeng, Jun Liu, Wenjing Wang, Liping Lin, Qingning Yang, Chuanming Li, Xinghua Liu:
Differentiation between COVID-19 and bacterial pneumonia using radiomics of chest computed tomography and clinical features. Int. J. Imaging Syst. Technol. 31(1): 47-58 (2021) - [j37]Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen:
Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan. Medical Image Anal. 67: 101824 (2021) - [j36]Donglin Di, Feng Shi, Fuhua Yan, Liming Xia, Zhanhao Mo, Zhongxiang Ding, Fei Shan, Bin Song, Shengrui Li, Ying Wei, Ying Shao, Miaofei Han, Yaozong Gao, He Sui, Yue Gao, Dinggang Shen:
Hypergraph learning for identification of COVID-19 with CT imaging. Medical Image Anal. 68: 101910 (2021) - [j35]Zekun Li, Wei Zhao, Feng Shi, Lei Qi, Xingzhi Xie, Ying Wei, Zhongxiang Ding, Yang Gao, Shangjie Wu, Jun Liu, Yinghuan Shi, Dinggang Shen:
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning. Medical Image Anal. 69: 101978 (2021) - [j34]Gaoping Liu, Zehong Cao, Qiang Xu, Qirui Zhang, Fang Yang, Xinyu Xie, Jingru Hao, Yinghuan Shi, Boris C. Bernhardt, Yichu He, Feng Shi, Guangming Lu, Zhiqiang Zhang:
Recycling diagnostic MRI for empowering brain morphometric research - Critical & practical assessment on learning-based image super-resolution. NeuroImage 245: 118687 (2021) - [j33]Kelei He, Wei Zhao, Xingzhi Xie, Wen Ji, Mingxia Liu, Zhenyu Tang, Yinghuan Shi, Feng Shi, Yang Gao, Jun Liu, Junfeng Zhang, Dinggang Shen:
Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images. Pattern Recognit. 113: 107828 (2021) - [c68]Mengkang Lu, Yongsheng Pan, Dong Nie, Feihong Liu, Feng Shi, Yong Xia, Dinggang Shen:
SMILE: Sparse-Attention based Multiple Instance Contrastive Learning for Glioma Sub-Type Classification Using Pathological Images. COMPAY@MICCAI 2021: 159-169 - [c67]Xiaodan Xing, Yixin Ma, Lei Jin, Tianyang Sun, Zhong Xue, Feng Shi, Jinsong Wu, Dinggang Shen:
A Multi-scale Graph Network with Multi-head Attention for Histopathology Image Diagnosisn. COMPAY@MICCAI 2021: 227-235 - [c66]Jie Wei, Feng Shi, Zhiming Cui, Yongsheng Pan, Yong Xia, Dinggang Shen:
Consistent Segmentation of Longitudinal Brain MR Images with Spatio-Temporal Constrained Networks. MICCAI (1) 2021: 89-98 - [c65]Zehong Cao, Feng Shi, Qiang Xu, Gaoping Liu, Tianyang Sun, Xiaodan Xing, Yichu He, Guangming Lu, Zhiqiang Zhang, Dinggang Shen:
Diagnosis of Hippocampal Sclerosis from Clinical Routine Head MR Images Using Structure-constrained Super-Resolution Network. MLMI@MICCAI 2021: 258-266 - [c64]Zhiming Cui, Changjian Li, Lei Yang, Chunfeng Lian, Feng Shi, Wenping Wang, Dijia Wu, Dinggang Shen:
VertNet: Accurate Vertebra Localization and Identification Network from CT Images. MICCAI (5) 2021: 281-290 - [c63]Mianxin Liu, Han Zhang, Feng Shi, Dinggang Shen:
Building Dynamic Hierarchical Brain Networks and Capturing Transient Meta-states for Early Mild Cognitive Impairment Diagnosis. MICCAI (7) 2021: 574-583 - [c62]Xukun Zhang, Zhiming Cui, Changan Chen, Jie Wei, Jingjiao Lou, Wenxin Hu, He Zhang, Tao Zhou, Feng Shi, Dinggang Shen:
Confidence-Aware Cascaded Network for Fetal Brain Segmentation on MR Images. MICCAI (3) 2021: 584-593 - [i16]Zekun Li, Wei Zhao, Feng Shi, Lei Qi, Xingzhi Xie, Ying Wei, Zhongxiang Ding, Yang Gao, Shangjie Wu, Jun Liu, Yinghuan Shi, Dinggang Shen:
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning. CoRR abs/2102.03837 (2021) - [i15]Gengxin Xu, Chen Liu, Jun Liu, Zhongxiang Ding, Feng Shi, Man Guo, Wei Zhao, Xiaoming Li, Ying Wei, Yaozong Gao, Chuan-Xian Ren, Dinggang Shen:
Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation. CoRR abs/2109.03478 (2021) - 2020
- [j32]Rui Hua, Quan Huo, Yaozong Gao, He Sui, Bing Zhang, Yu Sun, Zhanhao Mo, Feng Shi:
Segmenting Brain Tumor Using Cascaded V-Nets in Multimodal MR Images. Frontiers Comput. Neurosci. 14: 9 (2020) - [j31]Tao Zhou, Kim-Han Thung, Mingxia Liu, Feng Shi, Changqing Zhang, Dinggang Shen:
Multi-modal latent space inducing ensemble SVM classifier for early dementia diagnosis with neuroimaging data. Medical Image Anal. 60 (2020) - [j30]Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen:
Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis. Medical Image Anal. 63: 101709 (2020) - [j29]Hancan Zhu, Ehsan Adeli, Feng Shi, Dinggang Shen:
FCN Based Label Correction for Multi-Atlas Guided Organ Segmentation. Neuroinformatics 18(2): 319-331 (2020) - [j28]Liang Sun, Zhanhao Mo, Fuhua Yan, Liming Xia, Fei Shan, Zhongxiang Ding, Bin Song, Wanchun Gao, Wei Shao, Feng Shi, Huan Yuan, Huiting Jiang, Dijia Wu, Ying Wei, Yaozong Gao, He Sui, Daoqiang Zhang, Dinggang Shen:
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT. IEEE J. Biomed. Health Informatics 24(10): 2798-2805 (2020) - [j27]Xi Ouyang, Jiayu Huo, Liming Xia, Fei Shan, Jun Liu, Zhanhao Mo, Fuhua Yan, Zhongxiang Ding, Qi Yang, Bin Song, Feng Shi, Huan Yuan, Ying Wei, Xiaohuan Cao, Yaozong Gao, Dijia Wu, Qian Wang, Dinggang Shen:
Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia. IEEE Trans. Medical Imaging 39(8): 2595-2605 (2020) - [j26]Hengyuan Kang, Liming Xia, Fuhua Yan, Zhibin Wan, Feng Shi, Huan Yuan, Huiting Jiang, Dijia Wu, He Sui, Changqing Zhang, Dinggang Shen:
Diagnosis of Coronavirus Disease 2019 (COVID-19) With Structured Latent Multi-View Representation Learning. IEEE Trans. Medical Imaging 39(8): 2606-2614 (2020) - [c61]Wei Zhu, Feng Shi, Jiebo Luo:
Modeling Heterogeneity in Feature Selection for MCI Classification. ISBI 2020: 1548-1551 - [c60]Tong Li, Zhuochen Wang, Yanbo Chen, Lichi Zhang, Yaozong Gao, Feng Shi, Dahong Qian, Qian Wang, Dinggang Shen:
Two-Stage Mapping-Segmentation Framework for Delineating COVID-19 Infections from Heterogeneous CT Images. TIA@MICCAI 2020: 3-13 - [c59]Jianyuan Zhang, Feng Shi, Lei Chen, Zhong Xue, Lichi Zhang, Dahong Qian:
Ischemic Stroke Segmentation from CT Perfusion Scans Using Cluster-Representation Learning. MLCN/RNO-AI@MICCAI 2020: 67-76 - [c58]Xiaodan Xing, Lili Jin, Qinfeng Li, Lei Chen, Zhong Xue, Ziwen Peng, Feng Shi, Dinggang Shen:
Detection of Discriminative Neurological Circuits Using Hierarchical Graph Convolutional Networks in fMRI Sequences. UNSURE/GRAIL@MICCAI 2020: 121-130 - [c57]Bin Xiao, Naying He, Qian Wang, Zhong Xue, Lei Chen, Fuhua Yan, Feng Shi, Dinggang Shen:
Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer. MLMI@MICCAI 2020: 241-249 - [c56]Linlin Yao, Pengbo Jiang, Zhong Xue, Yiqiang Zhan, Dijia Wu, Lichi Zhang, Qian Wang, Feng Shi, Dinggang Shen:
Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling. MLMI@MICCAI 2020: 474-483 - [i14]Yuhua Chen, Anthony G. Christodoulou, Zhengwei Zhou, Feng Shi, Yibin Xie, Debiao Li:
MRI Super-Resolution with GAN and 3D Multi-Level DenseNet: Smaller, Faster, and Better. CoRR abs/2003.01217 (2020) - [i13]Feng Shi, Liming Xia, Fei Shan, Dijia Wu, Ying Wei, Huan Yuan, Huiting Jiang, Yaozong Gao, He Sui, Dinggang Shen:
Large-Scale Screening of COVID-19 from Community Acquired Pneumonia using Infection Size-Aware Classification. CoRR abs/2003.09860 (2020) - [i12]Zhenyu Tang, Wei Zhao, Xingzhi Xie, Zheng Zhong, Feng Shi, Jun Liu, Dinggang Shen:
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images. CoRR abs/2003.11988 (2020) - [i11]Feng Shi, Jun Wang, Jun Shi, Ziyan Wu, Qian Wang, Zhenyu Tang, Kelei He, Yinghuan Shi, Dinggang Shen:
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19. CoRR abs/2004.02731 (2020) - [i10]Xi Ouyang, Jiayu Huo, Liming Xia, Fei Shan, Jun Liu, Zhanhao Mo, Fuhua Yan, Zhongxiang Ding, Qi Yang, Bin Song, Feng Shi, Huan Yuan, Ying Wei, Xiaohuan Cao, Yaozong Gao, Dijia Wu, Qian Wang, Dinggang Shen:
Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia. CoRR abs/2005.02690 (2020) - [i9]Hengyuan Kang, Liming Xia, Fuhua Yan, Zhibin Wan, Feng Shi, Huan Yuan, Huiting Jiang, Dijia Wu, He Sui, Changqing Zhang, Dinggang Shen:
Diagnosis of Coronavirus Disease 2019 (COVID-19) with Structured Latent Multi-View Representation Learning. CoRR abs/2005.03227 (2020) - [i8]Liang Sun, Zhanhao Mo, Fuhua Yan, Liming Xia, Fei Shan, Zhongxiang Ding, Wei Shao, Feng Shi, Huan Yuan, Huiting Jiang, Dijia Wu, Ying Wei, Yaozong Gao, Wanchun Gao, He Sui, Daoqiang Zhang, Dinggang Shen:
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT. CoRR abs/2005.03264 (2020) - [i7]Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen:
Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan. CoRR abs/2005.03405 (2020) - [i6]Kelei He, Wei Zhao, Xingzhi Xie, Wen Ji, Mingxia Liu, Zhenyu Tang, Feng Shi, Yang Gao, Jun Liu, Junfeng Zhang, Dinggang Shen:
Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images. CoRR abs/2005.03832 (2020) - [i5]Donglin Di, Feng Shi, Fuhua Yan, Liming Xia, Zhanhao Mo, Zhongxiang Ding, Fei Shan, Shengrui Li, Ying Wei, Ying Shao, Miaofei Han, Yaozong Gao, He Sui, Yue Gao, Dinggang Shen:
Hypergraph Learning for Identification of COVID-19 with CT Imaging. CoRR abs/2005.04043 (2020) - [i4]Lei Lin, Feng Shi, Weizi Li:
Assessing Road Traffic Safety During COVID-19: Inequality, Irregularity, and Severity. CoRR abs/2011.02289 (2020)
2010 – 2019
- 2019
- [j25]Hancan Zhu, Feng Shi, Li Wang, Sheng-Che Hung, Meng-Hsiang Chen, Shuai Wang, Weili Lin, Dinggang Shen:
Dilated Dense U-Net for Infant Hippocampus Subfield Segmentation. Frontiers Neuroinformatics 13: 30 (2019) - [j24]Gang Li, Li Wang, Pew-Thian Yap, Fan Wang, Zhengwang Wu, Yu Meng, Pei Dong, Jaeil Kim, Feng Shi, Islem Rekik, Weili Lin, Dinggang Shen:
Computational neuroanatomy of baby brains: A review. NeuroImage 185: 906-925 (2019) - [j23]Ehsan Adeli, Kim-Han Thung, Le An, Guorong Wu, Feng Shi, Tao Wang, Dinggang Shen:
Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 515-522 (2019) - [j22]Feng Shi, Qi Yang, Xiuhai Guo, Touseef Ahmad Qureshi, Zixiao Tian, Huijuan Miao, Damini Dey, Debiao Li, Zhaoyang Fan:
Intracranial Vessel Wall Segmentation Using Convolutional Neural Networks. IEEE Trans. Biomed. Eng. 66(10): 2840-2847 (2019) - [j21]Yongqin Zhang, Feng Shi, Jian Cheng, Li Wang, Pew-Thian Yap, Dinggang Shen:
Longitudinally Guided Super-Resolution of Neonatal Brain Magnetic Resonance Images. IEEE Trans. Cybern. 49(2): 662-674 (2019) - [c55]Xiaodan Xing, Lili Jin, Feng Shi, Ziwen Peng:
Diagnosis of OCD using functional connectome and Riemann kernel PCA. Medical Imaging: Computer-Aided Diagnosis 2019: 109502C - [c54]Qingfeng Li, Quan Huo, Xiaodan Xing, Yiqiang Zhan, Xiang Sean Zhou, Feng Shi:
Spatial and depth weighted neural network for diagnosis of Alzheimer's disease. Medical Imaging: Computer-Aided Diagnosis 2019: 1095028 - [c53]Qingfeng Li, Xiaodan Xing, Ying Sun, Bin Xiao, Hao Wei, Quan Huo, Minqing Zhang, Xiang Sean Zhou, Yiqiang Zhan, Zhong Xue, Feng Shi:
Novel Iterative Attention Focusing Strategy for Joint Pathology Localization and Prediction of MCI Progression. MICCAI (4) 2019: 307-315 - [c52]Bin Xiao, Xiaoqing Cheng, Qingfeng Li, Qian Wang, Lichi Zhang, Dongming Wei, Yiqiang Zhan, Xiang Sean Zhou, Zhong Xue, Guangming Lu, Feng Shi:
Weakly Supervised Confidence Learning for Brain MR Image Dense Parcellation. MLMI@MICCAI 2019: 409-416 - [c51]Xiaodan Xing, Qingfeng Li, Hao Wei, Minqing Zhang, Yiqiang Zhan, Xiang Sean Zhou, Zhong Xue, Feng Shi:
Dynamic Spectral Graph Convolution Networks with Assistant Task Training for Early MCI Diagnosis. MICCAI (4) 2019: 639-646 - [c50]Hao Wei, Xiangyu Tang, Minqing Zhang, Qingfeng Li, Xiaodan Xing, Xiang Sean Zhou, Zhong Xue, Wenzhen Zhu, Zailiang Chen, Feng Shi:
Regression-Based Line Detection Network for Delineation of Largely Deformed Brain Midline. MICCAI (3) 2019: 839-847 - 2018
- [j20]Zhengwang Wu, Yaozong Gao, Feng Shi, Guangkai Ma, Valerie Jewells, Dinggang Shen:
Segmenting hippocampal subfields from 3T MRI with multi-modality images. Medical Image Anal. 43: 10-22 (2018) - [c49]Siming Yan, Feng Shi, Yuhua Chen, Damini Dey, Sang-Eun Lee, Hyuk-Jae Chang, Debiao Li, Yibin Xie:
Calcium removal from cardiac ct images using deep convolutional neural network. ISBI 2018: 466-469 - [c48]Yuhua Chen, Yibin Xie, Zhengwei Zhou, Feng Shi, Anthony G. Christodoulou, Debiao Li:
Brain MRI super resolution using 3D deep densely connected neural networks. ISBI 2018: 739-742 - [c47]Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen:
Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarchical Functional Connectivities from fMRI for Disease Diagnosis. MLMI@MICCAI 2018: 1-9 - [c46]Rui Hua, Quan Huo, Yaozong Gao, Yu Sun, Feng Shi:
Multimodal Brain Tumor Segmentation Using Cascaded V-Nets. BrainLes@MICCAI (2) 2018: 49-60 - [c45]Tao Zhou, Kim-Han Thung, Mingxia Liu, Feng Shi, Changqing Zhang, Dinggang Shen:
Multi-modal Neuroimaging Data Fusion via Latent Space Learning for Alzheimer's Disease Diagnosis. PRIME@MICCAI 2018: 76-84 - [c44]Yuhua Chen, Feng Shi, Anthony G. Christodoulou, Yibin Xie, Zhengwei Zhou, Debiao Li:
Efficient and Accurate MRI Super-Resolution Using a Generative Adversarial Network and 3D Multi-level Densely Connected Network. MICCAI (1) 2018: 91-99 - [c43]Jian Cheng, Tao Liu, Feng Shi, Ruiliang Bai, Jicong Zhang, Haogang Zhu, Dacheng Tao, Peter J. Basser:
On Quantifying Local Geometric Structures of Fiber Tracts. MICCAI (3) 2018: 392-400 - [c42]Li Wang, Gang Li, Feng Shi, Xiaohuan Cao, Chunfeng Lian, Dong Nie, Mingxia Liu, Han Zhang, Guannan Li, Zhengwang Wu, Weili Lin, Dinggang Shen:
Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis. MICCAI (3) 2018: 411-419 - [c41]Zhengwang Wu, Gang Li, Li Wang, Feng Shi, Weili Lin, John H. Gilmore, Dinggang Shen:
Registration-Free Infant Cortical Surface Parcellation Using Deep Convolutional Neural Networks. MICCAI (3) 2018: 672-680 - [i3]Yuhua Chen, Yibin Xie, Zhengwei Zhou, Feng Shi, Anthony G. Christodoulou, Debiao Li:
Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks. CoRR abs/1801.02728 (2018) - [i2]Siming Yan, Feng Shi, Yuhua Chen, Damini Dey, Sang-Eun Lee, Hyuk-Jae Chang, Debiao Li, Yibin Xie:
Calcium Removal From Cardiac CT Images Using Deep Convolutional Neural Network. CoRR abs/1803.00399 (2018) - [i1]Yuhua Chen, Feng Shi, Anthony G. Christodoulou, Zhengwei Zhou, Yibin Xie, Debiao Li:
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network. CoRR abs/1803.01417 (2018) - 2017
- [j19]Yan Wang, Guangkai Ma, Le An, Feng Shi, Pei Zhang, David S. Lalush, Xi Wu, Yi-Fei Pu, Jiliu Zhou, Dinggang Shen:
Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI. IEEE Trans. Biomed. Eng. 64(3): 569-579 (2017) - [c40]Khosro Bahrami, Islem Rekik, Feng Shi, Dinggang Shen:
Joint Reconstruction and Segmentation of 7T-like MR Images from 3T MRI Based on Cascaded Convolutional Neural Networks. MICCAI (1) 2017: 764-772 - 2016
- [j18]Ehsan Adeli, Feng Shi, Le An, Chong-Yaw Wee, Guorong Wu, Tao Wang, Dinggang Shen:
Joint feature-sample selection and robust diagnosis of Parkinson's disease from MRI data. NeuroImage 141: 206-219 (2016) - [j17]Le An, Pei Zhang, Ehsan Adeli-Mosabbeb, Yan Wang, Guangkai Ma, Feng Shi, David S. Lalush, Weili Lin, Dinggang Shen:
Multi-Level Canonical Correlation Analysis for Standard-Dose PET Image Estimation. IEEE Trans. Image Process. 25(7): 3303-3315 (2016) - [j16]Khosro Bahrami, Feng Shi, Xiaopeng Zong, Hae Won Shin, Hongyu An, Dinggang Shen:
Reconstruction of 7T-Like Images From 3T MRI. IEEE Trans. Medical Imaging 35(9): 2085-2097 (2016) - [j15]Yuyao Zhang, Feng Shi, Guorong Wu, Li Wang, Pew-Thian Yap, Dinggang Shen:
Consistent Spatial-Temporal Longitudinal Atlas Construction for Developing Infant Brains. IEEE Trans. Medical Imaging 35(12): 2568-2577 (2016) - [c39]Behrouz Saghafi, Geng Chen, Feng Shi, Pew-Thian Yap, Dinggang Shen:
Construction of Neonatal Diffusion Atlases via Spatio-Angular Consistency. Patch-MI@MICCAI 2016: 9-16 - [c38]Li Wang, Yaozong Gao, Gang Li, Feng Shi, Weili Lin, Dinggang Shen:
LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images. MCV/BAMBI@MICCAI 2016: 26-34 - [c37]Khosro Bahrami, Feng Shi, Islem Rekik, Dinggang Shen:
Convolutional Neural Network for Reconstruction of 7T-like Images from 3T MRI Using Appearance and Anatomical Features. LABELS/DLMIA@MICCAI 2016: 39-47 - [c36]Zhengwang Wu, Yaozong Gao, Feng Shi, Valerie Jewells, Dinggang Shen:
Automatic Hippocampal Subfield Segmentation from 3T Multi-modality Images. MLMI@MICCAI 2016: 229-236 - [c35]Khosro Bahrami, Islem Rekik, Feng Shi, Yaozong Gao, Dinggang Shen:
7T-Guided Learning Framework for Improving the Segmentation of 3T MR Images. MICCAI (2) 2016: 572-580 - 2015
- [j14]Gang Li, Li Wang, Feng Shi, John H. Gilmore, Weili Lin, Dinggang Shen:
Construction of 4D high-definition cortical surface atlases of infants: Methods and applications. Medical Image Anal. 25(1): 22-36 (2015) - [j13]Li Wang, Yaozong Gao, Feng Shi, Gang Li, John H. Gilmore, Weili Lin, Dinggang Shen:
LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images. NeuroImage 108: 160-172 (2015) - [c34]Le An, Pei Zhang, Ehsan Adeli-Mosabbeb, Yan Wang, Guangkai Ma, Feng Shi, David S. Lalush, Weili Lin, Dinggang Shen:
A Multi-level Canonical Correlation Analysis Scheme for Standard-Dose PET Image Estimation. Patch-MI@MICCAI 2015: 1-9 - [c33]Li Wang, Feng Shi, Yaozong Gao, Gang Li, Weili Lin, Dinggang Shen:
Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis. Patch-MI@MICCAI 2015: 28-36 - [c32]Shuyu Li, Feng Shi, Guangkai Ma, Minjeong Kim, Dinggang Shen:
Improving Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features Learned from Ultra-High Field MRI. Patch-MI@MICCAI 2015: 37-45 - [c31]Li Wang, Yaozong Gao, Feng Shi, Gang Li, Ken-Chung Chen, Zhen Tang, James J. Xia, Dinggang Shen:
Automated Segmentation of CBCT Image with Prior-Guided Sequential Random Forest. MCV@MICCAI 2015: 72-82 - [c30]Ehsan Adeli-Mosabbeb, Chong-Yaw Wee, Le An, Feng Shi, Dinggang Shen:
Joint Feature-Sample Selection and Robust Classification for Parkinson's Disease Diagnosis. MCV@MICCAI 2015: 127-136 - [c29]Yan Jin, Chong-Yaw Wee, Feng Shi, Kim-Han Thung, Pew-Thian Yap, Dinggang Shen:
Identification of Infants at Risk for Autism Using Multi-parameter Hierarchical White Matter Connectomes. MLMI 2015: 170-177 - [c28]Yuyao Zhang, Feng Shi, Pew-Thian Yap, Dinggang Shen:
Space-Frequency Detail-Preserving Construction of Neonatal Brain Atlases. MICCAI (2) 2015: 255-262 - [c27]Khosro Bahrami, Feng Shi, Xiaopeng Zong, Hae Won Shin, Hongyu An, Dinggang Shen:
Hierarchical Reconstruction of 7T-like Images from 3T MRI Using Multi-level CCA and Group Sparsity. MICCAI (2) 2015: 659-666 - [c26]Ehsan Adeli-Mosabbeb, Kim-Han Thung, Le An, Feng Shi, Dinggang Shen:
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis. NIPS 2015: 658-666 - 2014
- [j12]Gang Li, Li Wang, Feng Shi, Weili Lin, Dinggang Shen:
Simultaneous and consistent labeling of longitudinal dynamic developing cortical surfaces in infants. Medical Image Anal. 18(8): 1274-1289 (2014) - [j11]Li Wang, Feng Shi, Gang Li, Yaozong Gao, Weili Lin, John H. Gilmore, Dinggang Shen:
Segmentation of neonatal brain MR images using patch-driven level sets. NeuroImage 84: 141-158 (2014) - [j10]Li Wang, Feng Shi, Yaozong Gao, Gang Li, John H. Gilmore, Weili Lin, Dinggang Shen:
Integration of sparse multi-modality representation and anatomical constraint for isointense infant brain MR image segmentation. NeuroImage 89: 152-164 (2014) - [j9]Gang Li, Jingxin Nie, Li Wang, Feng Shi, John H. Gilmore, Weili Lin, Dinggang Shen:
Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces. NeuroImage 90: 266-279 (2014) - [c25]Li Wang, Yaozong Gao, Feng Shi, Gang Li, John H. Gilmore, Weili Lin, Dinggang Shen:
LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images. MCV 2014: 22-33 - [c24]Feng Shi, Jian Cheng, Li Wang, Pew-Thian Yap, Dinggang Shen:
Longitudinal Guided Super-Resolution Reconstruction of Neonatal Brain MR Images. STIA 2014: 67-76 - [c23]Gang Li, Li Wang, Feng Shi, Weili Lin, Dinggang Shen:
Constructing 4D Infant Cortical Surface Atlases Based on Dynamic Developmental Trajectories of the Cortex. MICCAI (3) 2014: 89-96 - [c22]Jiayin Kang, Yaozong Gao, Yao Wu, Guangkai Ma, Feng Shi, Weili Lin, Dinggang Shen:
Prediction of Standard-Dose PET Image by Low-Dose PET and MRI Images. MLMI 2014: 280-288 - 2013
- [j8]Yakang Dai, Feng Shi, Li Wang, Guorong Wu, Dinggang Shen:
iBEAT: A Toolbox for Infant Brain Magnetic Resonance Image Processing. Neuroinformatics 11(2): 211-225 (2013) - [c21]Li Wang, Feng Shi, Gang Li, Weili Lin, John H. Gilmore, Dinggang Shen:
Patch-driven neonatal brain MRI segmentation with sparse representation and level sets. ISBI 2013: 1090-1093 - [c20]Gang Li, Jingxin Nie, Li Wang, Feng Shi, John H. Gilmore, Weili Lin, Dinggang Shen:
Measuring longitudinally dynamic cortex development in infants by reconstruction of consistent cortical surfaces. ISBI 2013: 1380-1383 - [c19]Gang Li, Li Wang, Feng Shi, Weili Lin, Dinggang Shen:
Multi-atlas Based Simultaneous Labeling of Longitudinal Dynamic Cortical Surfaces in Infants. MICCAI (1) 2013: 58-65 - [c18]Feng Shi, Jian Cheng, Li Wang, Pew-Thian Yap, Dinggang Shen:
Low-Rank Total Variation for Image Super-Resolution. MICCAI (1) 2013: 155-162 - [c17]Li Wang, Ken-Chung Chen, Feng Shi, Shu Liao, Gang Li, Yaozong Gao, Steve G. Shen, Jin Yan, Philip K. M. Lee, Ben Chow, Nancy X. Liu, James J. Xia, Dinggang Shen:
Automated Segmentation of CBCT Image Using Spiral CT Atlases and Convex Optimization. MICCAI (3) 2013: 251-258 - [c16]Li Wang, Feng Shi, Gang Li, Weili Lin, John H. Gilmore, Dinggang Shen:
Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain Segmentation. MICCAI (1) 2013: 703-710 - 2012
- [j7]Feng Shi, Pew-Thian Yap, Wei Gao, Weili Lin, John H. Gilmore, Dinggang Shen:
Altered structural connectivity in neonates at genetic risk for schizophrenia: A combined study using morphological and white matter networks. NeuroImage 62(3): 1622-1633 (2012) - [j6]Feng Shi, Li Wang, Yakang Dai, John H. Gilmore, Weili Lin, Dinggang Shen:
LABEL: Pediatric brain extraction using learning-based meta-algorithm. NeuroImage 62(3): 1975-1986 (2012) - [c15]Li Wang, Feng Shi, Gang Li, Dinggang Shen:
4D Segmentation of Longitudinal Brain MR Images with Consistent Cortical Thickness Measurement. STIA 2012: 63-75 - [c14]Feng Shi, Li Wang, Guorong Wu, Yu Zhang, Manhua Liu, John H. Gilmore, Weili Lin, Dinggang Shen:
Atlas Construction via Dictionary Learning and Group Sparsity. MICCAI (1) 2012: 247-255 - 2011
- [j5]Yong Fan, Feng Shi, Jeffrey Keith Smith, Weili Lin, John H. Gilmore, Dinggang Shen:
Brain anatomical networks in early human brain development. NeuroImage 54(3): 1862-1871 (2011) - [j4]Martha Skup, Hongtu Zhu, Yaping Wang, Kelly S. Giovanello, Ja-an Lin, Dinggang Shen, Feng Shi, Wei Gao, Weili Lin, Yong Fan, Heping Zhang:
Sex differences in grey matter atrophy patterns among AD and aMCI patients: Results from ADNI. NeuroImage 56(3): 890-906 (2011) - [j3]Li Wang, Feng Shi, Weili Lin, John H. Gilmore, Dinggang Shen:
Automatic segmentation of neonatal images using convex optimization and coupled level sets. NeuroImage 58(3): 805-817 (2011) - [c13]Li Wang, Feng Shi, Pew-Thian Yap, John H. Gilmore, Weili Lin, Dinggang Shen:
Accurate and Consistent 4D Segmentation of Serial Infant Brain MR Images. MBIA 2011: 93-101 - [c12]Feng Shi, Li Wang, John H. Gilmore, Weili Lin, Dinggang Shen:
Learning-Based Meta-Algorithm for MRI Brain Extraction. MICCAI (3) 2011: 313-321 - [c11]Yaping Wang, Jingxin Nie, Pew-Thian Yap, Feng Shi, Lei Guo, Dinggang Shen:
Robust Deformable-Surface-Based Skull-Stripping for Large-Scale Studies. MICCAI (3) 2011: 635-642 - 2010
- [j2]Feng Shi, Yong Fan, Songyuan Tang, John H. Gilmore, Weili Lin, Dinggang Shen:
Neonatal brain image segmentation in longitudinal MRI studies. NeuroImage 49(1): 391-400 (2010) - [j1]Feng Shi, Pew-Thian Yap, Yong Fan, John H. Gilmore, Weili Lin, Dinggang Shen:
Construction of multi-region-multi-reference atlases for neonatal brain MRI segmentation. NeuroImage 51(2): 684-693 (2010) - [c10]Feng Shi, Pew-Thian Yap, Yong Fan, John H. Gilmore, Weili Lin, Dinggang Shen:
Neonatal brain MRI segmentation by building multi-region-multireference atlases. ISBI 2010: 964-967 - [c9]Li Wang, Feng Shi, John H. Gilmore, Weili Lin, Dinggang Shen:
Automatic Segmentation of Neonatal Images Using Convex Optimization and Coupled Level Set Method. MIAR 2010: 1-10 - [c8]Feng Shi, Pew-Thian Yap, John H. Gilmore, Weili Lin, Dinggang Shen:
Spatial-Temporal Constraint for Segmentation of Serial Infant Brain MR Images. MIAR 2010: 42-50 - [c7]Yang Li, Yaping Wang, Zhong Xue, Feng Shi, Weili Lin, Dinggang Shen:
The Alzheimer's Disease Neuroimaging Initiative: Consistent 4D Cortical Thickness Measurement for Longitudinal Neuroimaging Study. MICCAI (2) 2010: 133-142 - [c6]Pahal Dalal, Feng Shi, Dinggang Shen, Song Wang:
Multiple Cortical Surface Correspondence Using Pairwise Shape Similarity. MICCAI (1) 2010: 349-356
2000 – 2009
- 2009
- [c5]Feng Shi, Pew-Thian Yap, Yong Fan, Jie-Zhi Cheng, Lawrence L. Wald, Guido Gerig, Weili Lin, Dinggang Shen:
Cortical enhanced tissue segmentation of neonatal brain MR images acquired by a dedicated phased array coil. CVPR Workshops 2009: 39-45 - [c4]Feng Shi, Yong Fan, Songyuan Tang, John H. Gilmore, Weili Lin, Dinggang Shen:
Brain tissue segmentation of neonatal MR images using a longitudinal subject-specific probabilistic atlas. Medical Imaging: Image Processing 2009: 725942 - 2008
- [c3]Yuanchao Zhang, Jiefeng Jiang, Lei Lin, Feng Shi, Yuan Zhou, Chunshui Yu, Kuncheng Li, Tianzi Jiang:
A Surface-Based Fractal Information Dimension Method for Cortical Complexity Analysis. MIAR 2008: 133-141 - 2007
- [c2]Tianzi Jiang, Feng Shi, Wanlin Zhu, Shuyu Li, Xiaobo Li:
Shape Analysis of Human Brain with Cognitive Disorders. HCI (12) 2007: 409-414 - [c1]Feng Shi, Yong Liu, Tianzi Jiang, Yuan Zhou, Wanlin Zhu, Jiefeng Jiang, Haihong Liu, Zhening Liu:
Regional Homogeneity and Anatomical Parcellation for fMRI Image Classification: Application to Schizophrenia and Normal Controls. MICCAI (2) 2007: 136-143
Coauthor Index
[j53] [j51] [j49] [j48] [j47] [j46] [j45] [c83] [c82] [c81] [c79] [c78] [c77] [c76] [c75] [c74] [i20] [j43] [j42] [j41] [c73] [c71] [c70] [c69] [i17] [j40] [j39] [j37] [j36] [j35] [j33] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [i16] [i15] [j31] [j30] [j29] [j28] [j27] [j26] [c60] [c58] [c57] [c56] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [j25] [j24] [j23] [j21] [j20] [c47] [c45] [c42] [c41] [j19] [c40] [j18] [j17] [j16] [j15] [c39] [c38] [c37] [c36] [c35] [j14] [j13] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [j12] [j11] [j10] [j9] [c25] [c24] [c23] [c22] [j8] [c21] [c20] [c19] [c18] [c17] [c16] [j7] [j6] [c15] [c14] [j5] [j4] [j3] [c13] [c12] [c11] [j2] [j1] [c10] [c9] [c8] [c7] [c6] [c5] [c4]
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